BRAIN FINGERPRINTING
ABSTRACT
Brain fingerprinting is based on finding that the brain generates a unique brain wave pattern when a person encounters a familiar stimulus Use of functional magnetic resonance imaging in lie detection derives from studies suggesting that persons asked to lie show different patterns of brain activity than they do when being truthful. Issues related to the use of such evidence in courts are discussed. The author concludes that neither approach is currently supported by enough data regarding its accuracy in detecting deception to warrant use in court.
In the field of criminology, a new lie detector has been developed in the United States of America. This is called “brain fingerprinting”. This invention is supposed to be the best lie detector available as on date and is said to detect even smooth criminals who pass the polygraph test (the conventional lie detector test) with ease. The new method employs brain waves, which are useful in detecting whether the person subjected to the test, remembers finer details of the crime. Even if the person willingly suppresses the necessary information, the brain wave is sure to trap him, according to the experts, who are very excited about the new kid on the block.
INTRODUCTION
Brain Fingerprinting is a controversial proposed investigative technique that measures recognition of familiar stimuli by measuring electrical brain wave responses to words, phrases, or pictures that are presented on acomputer screen. Brain fingerprinting was invented by Lawrence Farwell. The theory is that the suspect’s reaction to the details of an event or activity will reflect if the suspect had prior knowledge of the event or activity. This test uses what Farwell calls the MERMER (“Memory and Encoding Related Multifaceted Electroencephalographic Response”) response to detect familiarity reaction. One of the applications is lie detection. Dr. Lawrence A. Farwell has invented, developed, proven, and patented the technique of Farwell Brain Fingerprinting, a new computer-based technology to identify the perpetrator of a crime accurately and scientifically by measuring brain-wave responses to crime-relevant words or pictures presented on a computer screen. Farwell Brain Fingerprinting has proven 100% accurate in over 120 tests, including tests on FBI agents, tests for a US intelligence agency and for the US Navy, and tests on real-life situations including actual crimes..
What is Brain Fingerprinting?
Brain Fingerprinting is designed to determine whether an individual recognizes specific information related to an event or activity by measuring electrical brain wave responses to words, phrases, or pictures presented on a computer screen. The technique can be applied only in situations where investigators have a sufficient amount of specific information about an event or activity that would be known only to the perpetrator and investigator. In this respect, Brain Fingerprinting is considered a type of Guilty Knowledge Test, where the “guilty” party is expected to react strongly to the relevant detail of the event of activity.
Existing (polygraph) procedures for assessing the validity of a suspect’s “guilty” knowledge rely on measurement of autonomic arousal (e.g., palm sweating and heart rate), while Brain Fingerprinting measures electricalbrain activity via a fitted headband containing special sensors. Brain Fingerprinting is said to be more accurate in detecting “guilty” knowledge distinct from the false positives of traditional polygraph methods, but this is hotly disputed by specialized researchers.
Technique:
The person to be tested wears a special headband with electronic sensors that measure the electroencephalography from several locations on the scalp. In order to calibrate the brain fingerprinting system, the testee is presented with a series of irrelevant stimuli, words, and pictures, and a series of relevant stimuli, words, and pictures. The test subject’s brain response to these two different types of stimuli allow the testor to determine if the measured brain responses to test stimuli, called probes, are more similar to the relevant or irrelevant responses.
NANO GENERATOR TO POWER NANO DEVICES
ABSTRACT
Materials Science research is now entered a new phase where the structure and properties of materials are investigated, characterized and controlled at the nanoscale. Though as sophisticated as their larger counterparts, these devices are still burdened because they rely on an outside power. The size of the entire device is determined by the size of the power source. Batteries and other traditional sources are too large, and tend to negate the size advantages of nano devices. Also, batteries being used at present require toxic chemicals and have to be replaced periodically.
To overcome these challenges; researchers are finding alternative ways to power nano devices. One promising development is the nano generator. In this talk, we specially emphasized application of nano generators, importance of nanowires in building a nano generator. Nanogenerator allows us to harvest or recycle energy from many sources to power these devices. The nanogenerators take advantage of the unique coupled piezoelectric and semiconducting properties of zinc oxide nanostructures, which produce small electrical charges when they are flexed.
KEYWORDS
Nano wire,
Low power miniature sensors,
Piezoelectric effect,
Electric power,
VIBES (Vibration Energy Scavenging)
INTRODUCTION
An array of zinc-oxide nanowires that generates current when vibrated with ultrasonic waves could provide a new way to power biological sensors and nano devices. Using ultrasonic waves to vibrate an array of zinc-oxide nanowires, researchers at Georgia Tech have made a tiny generator that can produce direct current. . By taking advantage of the fact that zinc-oxide nano wires are piezoelectric, they converted mechanical energy into electricity. And by finding a way to collect electricity from multiple nano wires, the researchers took a big step toward a practical nano-scale power generator.
NANOWIRE
Nanowires and other nano materials have shown great promise in creating future generations of electronic devices. New work from researchers at NIST, George Mason University, and Kwangwoon University in Seoul has generated a hybrid memory device that uses both conventional techniques and exploits the properties of silicon nanowires.
Picture shows----
Electron micrograph shows the gallium nitride wires growing on a silicon substrate (color added for contrast.)
The hybrid structure exhibited by these devices means that they are more reliable than other nanowire approaches, and they should be easier to integrate into modern components. The hybrid device that the team built is a non-volatile memory device similar to a flash device, which retains its memory even when power is turned off.
The wires are generally between 30 and 500 nanometers (nm) in diameter and up to 12 micrometers long. When excited with a laser or electric current, the wires emit an intense glow in the ultraviolet or visible parts of the spectrum, depending on the alloy composition.
KEYWORDS
Nano wire,
Low power miniature sensors,
Piezoelectric effect,
Electric power,
VIBES (Vibration Energy Scavenging)
INTRODUCTION
An array of zinc-oxide nanowires that generates current when vibrated with ultrasonic waves could provide a new way to power biological sensors and nano devices. Using ultrasonic waves to vibrate an array of zinc-oxide nanowires, researchers at Georgia Tech have made a tiny generator that can produce direct current. . By taking advantage of the fact that zinc-oxide nano wires are piezoelectric, they converted mechanical energy into electricity. And by finding a way to collect electricity from multiple nano wires, the researchers took a big step toward a practical nano-scale power generator.
NANOWIRE
Nanowires and other nano materials have shown great promise in creating future generations of electronic devices. New work from researchers at NIST, George Mason University, and Kwangwoon University in Seoul has generated a hybrid memory device that uses both conventional techniques and exploits the properties of silicon nanowires.
Picture shows----
Electron micrograph shows the gallium nitride wires growing on a silicon substrate (color added for contrast.)
The hybrid structure exhibited by these devices means that they are more reliable than other nanowire approaches, and they should be easier to integrate into modern components. The hybrid device that the team built is a non-volatile memory device similar to a flash device, which retains its memory even when power is turned off.
The wires are generally between 30 and 500 nanometers (nm) in diameter and up to 12 micrometers long. When excited with a laser or electric current, the wires emit an intense glow in the ultraviolet or visible parts of the spectrum, depending on the alloy composition.
The nanowires are grown onto an oxide-nitride-oxide substrate. When positive voltage is applied, electrons tunnel down into the substrate; when negative voltage is applied, the electrons tunnel back into the wires. When no voltage is present, the device can be read, and the position of the electrons will represent a "1" or a "0".
WHAT IS A NANO GENERATOR
Generation of electricity is necessary for some extremely small devices (nano devices) like medical devices, sensors and portable electronics without the need for bulky batteries or other energy sources. Instead of batteries, electricity for such devices would come, for instance, from muscle contraction or other body movements. Nano generator is one such device. Zinc oxide nanowires in nano generator produce electricity via a long-known phenomenon termed the piezoelectric effect. It occurs in certain materials, which change mechanical energy -- from flexing or twisting, for instance -- into electricity.
HOW IT WORKS
A key innovation that led to the nano wire generator is a new electrode design. Fabrication begins with growing an array of vertically-aligned nanowires approximately half a micron apart on gallium arsenide, sapphire or flexible polymer substrate.
Picture shows---
Zinc oxide nanowires grown on a gallium nitride substrate
A layer of zinc oxide is grown on top of the substrate to collect the current. Also fabricated is a ‘zigzag’ silicon electrode that contains thousands of nano-scale tips made conductive by a platinum coating. The electrode is then lowered on top of the nano wire array, leaving just enough space so that a significant number of the nano wires are free to flex with in the gaps created by the tips.
Moved by mechanical energy such as waves or vibration, the nanowires periodically contact the tips, transferring there electrical charges. To vibrate the electrode, the researchers packaged the device, put it in water and exposed to the ultrasonic waves. As the zigzag electrode moves up and down, its peaks push and bend the nano wires, which generate electric current that the electrode collects simultaneously. Compressing the wires or vibrating them left or right makes all the current add up in the same direction. By capturing the tiny amounts of current produced by hundreds of nano wires kept in motion, the generator outputs a direct current in the nano-ampere range.
Before that happens, additional development will be needed to optimize current production. For instance, though nanowires in the arrays can be grown to approximately the same length -- about one micron -- there is some variation. Wires that are too short cannot touch the electrode to produce current, while wires that are too long cannot flex to produce electrical charge.
However, for real-world applications, the current generated by the nano generator needs to be higher and more stable. Wang’s research group is working on improvements toward that goal. . Wires that are too short cannot touch the electrode to produce current, while wires that are too long cannot flex to produce electrical charge. Right now, the nano
Researchers say that the next step is to grow a more regular array of nanowires that are uniform in size and height. Matching the nanowire pattern with the pattern on the electrode would utilize all the nanowires, increasing the current output and making it more stable. The research team also needs to increase the generator’s lifetime as it runs for a little more than an hour right now.
A graph showing spikes of electrical discharge as the nanowires are scanned.
POSSIBLE APPLICATIONS
The nano generator could provide a new way to power biological sensors and nano devices. It could drive them by making use of wind energy or liquid flow, eliminating the need for external batteries.
Current battery technology limits the use of microelectromechanical sensors that measure cancer biomarkers, blood pH and glucose. The reason: as these sensors get smaller and smaller, conventional chemical batteries can’t keep up. Most of the time it’s the battery that’s big compared to the sensing part and it also runs out of power.
Our bodies are good at converting chemical energy from glucose into the mechanical energy of our muscles. These nanogenerators can take that mechanical energy and convert it to electrical energy for powering devices inside the body.
The nano wire generator looks like a promising answer; it’s a small power source that doesn’t need refilling. One important application of the nano generator can be powering implantable biological sensors. Implanted in the body and driven by muscle contractions, blood flow or external vibrations transmitted through tissues, it could power the sensors.
FUTURE SCOPE
Researchers expect that with optimization, the nano generator could produce as much as 4 watts per cubic centimeter based on a calculation for a single nano wire. This would be enough to power a broad range of nano-scale defence, environmental and biomedical applications, including biosensors implanted in the body, environmental monitors and even nano scale robots.
The team expects to make as many as millions or even billions of nanowires produce current simultaneously, which will allow optimization of operation of nano generator. Producing the top electrode as a single assembly sets the stage for scaling up this technology to power real nano scale applications. Before that happens, additional development will be needed to optimize current production by controlling the growth, density and uniformity of the wires.
Because the chemical process by which the wires can be grown is inexpensive, at some point it may be practical to produce large arrays that are capable of providing enough power for consumer electronics. We can grow these on polymer substrates at very low cost, so that one day by placing these into people's shoes we can generate electricity when walking.
To power a simple electronic device such as a diode or a transistor, the need is to raise the charge on the device from its current milli volt to at least half a volt. Thus, researchers plan to make the nanowires more uniform and stack multiple arrays as well as add capacitors to accumulate charge.
Because zinc oxide is non-toxic and compatible with the body, the nano generators could be integrated into implantable biomedical devices to wirelessly measure blood flow and blood pressure within the body. They could also find moue ordinary applications in generating small current to power small body electronics. Finally, anything that makes the nanowires move within the generator can be used for generating power.
INTRODUCTION
THE ELECTROMAGNETIC SPECTRUM
To start with, to know what a spectrum is: when white light is shone through a prism it is separated out into all the colours of the rainbow; this is the visible spectrum. So white light is a mixture of all colours. Black is NOT a colour; it is what you get when all the light is taken away.
Some physicists pretend that light consists of tiny particles which they call
photons. They travel at the speed of light (what a surprise). The speed of light is about
300,000,000 meters per second. When they hit something they might bounce off, go right
through or get absorbed. What happens depends a bit on how much energy they have. If
they bounce off something and then go into your eye you will "see" the thing they have
bounced off. Some things like glass and Perspex will let them go through; these materials
are transparent. Black objects absorb the photons so you should not be able to see black
things: you will have to think about this one. These poor old physicists get a little bit
confused when they try to explain why some photons go through a leaf, some are
reflected, and some are absorbed. They say that it is because they have different amounts
of energy.
Other physicists pretend that light is made of waves. These physicists measure the length of the waves and this helps them to explain what happens when light hits leaves. The light with the longest wavelength (red) is absorbed by the green stuff (chlorophyll) in the leaves. So is the light with the shortest wavelength (blue). In between these two colours there is green light, this is allowed to pass right through or is reflected. (Indigo and violet have shorter wavelengths than blue light.)
Well it is easy to explain some of the properties of light by pretending that it is made of tiny particles called photons and it is easy to explain other properties of light by pretending that it is some kind of wave.
The visible spectrum is just one small part of the electromagnetic spectrum. These electromagnetic waves are made up of two parts. The first part is an electric field. The second part is a magnetic field. So that is why they are called electromagnetic waves. The two fields are at right angles to each other.
THE MICROWAVE REGION
TRANSMITTER DESIGN
Abstract
With the furtherance of technology, life is becoming simpler and less demanding. The conglomeration of three major disciplines, Computers, Communications and Electronics unleashes a vast amount of power in terms of technology. In an era of cost-cutting ,when companies are faced with a growing need to maximize and/or improve efficiencies of existing IT investments, organizations are turning to Grid Computing as a strategic solution.
This paper seeks to introduce this Grid Computing as an emerging computing model that provides the ability to perform higher throughput computing by taking advantage of many networked computers to model virtual computer architecture.
Further, it enumerates on how the Grids use the resources of many separate computers connected through a network to solve large-scale computation problems. It explains how the Grids provide the ability to perform computations on large data sets, by breaking them down into many smaller ones, or provide the ability to perform many more computations at once than would be possible on a single computer, by modeling a parallel division of labor between processes.
Finally the paper puts forth the Future of Grid Computing with a case-study and enlightens on how organizations can optimize computing and data resources, pool them for large capacity workloads, share them across networks and enable collaboration.
1.Introduction
Because it is an emerging technology, grid computing can mean different things to different people.
“Grid computing allows you to unite pools of servers, storage systems, and networks into a single large system so that you can deliver the power of multiple-systems resources to a single user point for a specific purpose.” To a user, data file, or an application, the system appears to be a single enormous virtual computing system.
3.Grid Network
3.1 A Simple Grid Network:
Illusion of a Virtual Computing Environment
Grid computing is the next logical step in distributed networking. A simple Grid Network contains a Grid Software which acts as an interface between any user (normal user, administrator) and the virtual computing environment (a superset of PC’s, Workstations, Super Computers).
3.2 Components of Grid Network:
Clusters, Workstations, Desktop PC’s, Super Computers contribute to the components of a grid. Each component might be an important component of a grid, but by itself doesn’t constitute a grid.
4.Evolution of GridIn fact, grid can be seen as the latest and most complete evolution of more familiar developments — such as distributed computing, the Web, peer-to-peer computing and virtualization technologies.
4.1 The Time Is Right:Many organizations feel that this is the right time to encourage Grid Computing for the following reasons:
- Unprecedented pressure to lower costs
- Inexpensive, commodity blade servers
- Inexpensive OS optimized for1-4CPUs
- Storage no longer tied to a single server
5.Functions
When you deploy a grid, it will be to meet a set of customer requirements. To better match grid computing capabilities to those requirements, it is useful to keep in mind the reasons for using grid computing. This section describes the most important capabilities of grid computing.
5.1 Optimal usage of resources:
Remote Applicability: The easiest use of grid computing is to run an existing application on a different machine.
Utility of un-used disk drive: Grid computing can be used to aggregate the unused storage into a much larger virtual data store.
Resource Utilization: Many resources such as CPU, Storage and so on, can be used with the principle of optimality.
5.2. Parallel CPU capacity:A CPU intensive grid application can be thought of as many smaller “sub jobs,” each executing on a different machine in the grid. For example, a job finishes 10 times faster if it uses 10 times the number of processors.
5.3 Virtual resources and virtual organizations for Collaboration:
In the past, distributed computing promised collaboration among a wider audience, and achieved it to some extent. Grid computing can take these capabilities to an even wider audience, while offering important standards that enable very heterogeneous systems to work together to form the image of a large virtual computing system offering a variety of resources.
5.4 Access to additional resources:
In addition to CPU and storage resources, a grid can provide access to other resources in additional numbers and/or capacity.
5.5 Resource balancing:
For applications that are grid-enabled, the grid can offer a resource balancing effect by scheduling grid jobs on machines with low utilization. Without a grid infrastructure, balancing decisions are difficult to prioritize and execute.
5.6 Reliability And Management:As there are various supplementary resources available for each resource, reliability is achieved to a greater extent.
The Grid software itself takes care of all the management among the various Grid components.
6.Grid Architecture
6.1 Layers of Grid Architecture:
• Fabric Layer: It provides access to some shared resources using Grid Protocols. Shared Resources can be computational resources, storage systems, catalogs, network resources, and sensors.
• Connectivity Layer: It defines the core communication and authentication protocols required for grid-specific network functions.
• Resources Layer: It defines protocols for secure negotiations, initiation and monitoring the control of sharing operations on individual resources. Information and management protocols define this layer.
• Collective Layer: It contains protocols and services that capture interactions among a collection of resources.
• Application Layer: User applications operate in this layer by using the services of other layers.
6.2 Grid Topology:
Intra grid:A typical intra grid topology exists within a single organization. The primary characteristics of an intra grid are a single security provider, bandwidth on the private network is high and always available, and there is a single environment within a single network.
Extra grid:Based on a single organization, the extra grid expands on the concept by bringing together two or more intra grids. An extra grid, typically involves more than one security provider, and the level of management complexity increases. The primary characteristics of an extra grid are dispersed security, multiple organizations, and WAN connectivity.
Inter grid:The primary characteristics of an inter grid include dispersed security, multiple organizations, and WAN connectivity. The data in an inter grid is global public data, and applications must be modified for a global audience.
6.3 Grid Software:
There are many aspects to grid computing that typically are controlled through software. These functions can be handled across a spectrum of very manual procedures to processes being handled through sophisticated software.
Donor software
Management Software
Communications Software
Schedulers Software
7.Grid Security
In a grid, the member machines are configured to execute programs rather than moving data. This makes an unsecured grid potentially fertile ground for viruses and Trojan horse programs. For this reason, it is important to understand which components of the grid must be rigorously secured. The high level grid security requirements are:
Authorization
Privacy
Confidentiality
Manageability
Firewall
8.Case Study
Work-Flow:
• This processor initially checks if the task is too large for a single processor to handle.
• If so, distributes the task among various devices of the grid, here comes the aspect of Parallel CPU Capacity. The processors job is to collect the Incoming data files and this is simply done through WAN/Internet.
• The Annual Incomes of the employees starts getting accumulated in the disk drive of the processor. Once there is no more disk space left with it, it has a privilege of using the storage device that has been idle for the past few hours in the same grid network; the functional Application Exploiting under Utilized Resources is taken advantage of at this point.
• Suppose a high priority task has been assigned to this device, it has a capability to transfer the relatively low priority task to some other device of the network and can finish its high priority task as per the dead line, thereby Utilizing Resources.
9.Conclusion
It is important to know that grid is not a silver bullet that can take any application and run it a 1000 times faster without the need for buying any more machines or software. Grid computing appears to be a promising trend for three reasons:
(1) Its ability to make more cost-effective use of a given amount of computer resources.
(2) As a way to solve problems that can't be approached without an enormous amount of computing power.
(3) Because it suggests that the resources of many computers can be cooperatively and perhaps synergistically harnessed and managed as collaboration towards a common objective.
Definitions
A modern operating system uses multiprogramming, virtual memory, and file systems to share CPU, memory, and disk resources among multiple processes and users. Each process accesses the physical resources indirectly, through abstractions provided by the operating system. Contemporaneous to the development of these mechanisms was that of another resource-sharing approach, virtual machines. A virtual machine presents the view of a duplicate of the underlying physical machine to the software that runs within it, allowing multiple operating systems to run concurrently and multiplex resources of a computer - processor, memory, disk, and network. Virtual machines can be divided into two main categories: those that virtualize a complete instruction set architecture (ISA-VMs) including both user and system instructions, and those that support an application binary interface (ABI-VMs) with virtualization of system calls. An important class of virtual machines (“classic” VMs) consists of ISA-VMs that support same-ISA execution of entire operating systems. A classic virtual machine abstraction allows for great flexibility in supporting multiple operating systems and is the focus of this paper.
Advantages
Unlike conventional operating systems, classic VMs allow dynamic multiplexing of users onto physical resources at the granularity of a single user per operating system session, thereby supporting per-user VMconfiguration and isolation from other users sharing the same physical resource. In the remainder of this section we focus on a scenario where each dynamic instance of a classic VM is dedicated to a single logical user.
1. Security and isolation
2. Customization
3. Administrator privileges
4. Resource control
5. Performance considerations
The advantages of virtual machines are for naught if they can not deliver sufficient performance. Virtual machine monitors incur performance overheads when applications within a VM execute privileged instructions that must be trapped and emulated. These are typically issued by kernel code of “guest” VMs during system calls, virtual memory handling, context switches and I/O. User-level code within VMMs runs directly on hardware without translation overheads. The overall overhead incurred by VMs thus depends on system characteristics, including the processor’s ISA, the VMM architecture and implementation, and the type of workload running in the system.
Table 1. Macrobenchmark results. User, system and total times are reported for three scenarios: physical machine, VM with state in local disk, VM with state accessed via NFS-based grid virtual file system (PVFS). Overheads are calculated using execution times and the physical machine as reference. In the PVFS scenario, the physical and data servers are located at Northwestern University, while the image server is located at the University of Florida.
Figure 1. Microbenchmark results: slowdown of synthetic test task under presence of background load for twelve different scenarios.
Table 2. Average, standard deviation, minimum and maximum VM startup times. Virtual machine sessions are instantiated using globusrun (Globus 2.0 toolkit) within a LAN. Measurements have been taken across 10 samples. Time (in seconds) is measured as wall-clock execution time from the beginning to the end of the execution of globusrun.
Middleware challenges
1. Data management
Data management is a key technology for VM-based grid computing, enabling administrative decoupling of computation providers and users. Data management involves: the transfer of VM images so that a user’s virtual machine can be instantiated anywhere and migrated when necessary, and support for location-independent access to user files. With appropriate data management support, computation, state, and user data can reside in different domains.
The components of a virtual machine session are distributed across three different logical entities: image servers, which provide the capability of archiving static VM states; computation servers (or VM hosts), which provide the capability of instantiating dynamic VM images (or VM guests); and data servers, which provide the capability of storing user data. In this scenario, VM state information needs to be transferred from an image server to a VM host (where it is instantiated), and from a data server to the VM guest (where it is processed) as in Figure 2.
High performance data transfers: Fast and simple access to images and user data is critical. Current grid solutions, such as Globus [4, 1] and PBS [3] typically employ file-staging techniques to transfer files between user accounts in the absence of a common file system.
Figure 3. Architecture for a VM-based grid service. In 1- 6, a virtual machine (V4) is dynamically created by middleware front-end F on behalf of user X. This VM is dedicated to a single user. In another scenario, virtual machines V1, V2 are instantiated on P2 on behalf of a service provider S, and are multiplexed across users A, B, C and applications provided by S. The logical user account abstraction decouples access to physical resources (middleware) from access to virtual resources (end-users and services).
In the following we lay out initial software architecture for virtual machine grid computing by describing the life cycle of a VM within it.
1. A user X (or grid middleware F on their behalf) first consults an information service, querying for a VM future (a physical machine able to instantiate a dynamic VM) P that meets their needs.
2. If necessary, X also consults an information service to query for a VM image server I with a base O/S installation that meets their application needs. Alternatively, users may provide VM images of their own (e.g. a customized O/S installation).
3. The middleware then establishes a data session between the physical server P and the image server I to allow for the instantiation of a dynamic VM. This data connection can be established via explicit transfers (e.g. Grid FTP) or via implicit, on-demand transfers (e.g. a grid virtual file system, Figure 2).
4. Once the data session for image I is established, the user can negotiate with the physical machine the startup of a VM instance Vi (e.g. using Globus GRAM or SSH). The virtual machine Vi may start from a preboot (cold) state, or from a post-boot (warm) state stored as part of the image. In addition, upon startup, the VM is assigned an IP address (via DHCP, or by connecting to a virtual network).
5. Once the VM instance Vi is running and on the network, additional data sessions are established. These connect the O/S within Vi to application server A and to the user’s data server D. As previously, these sessions can be realized with explicit or implicit transfers (Figure 2).
6. The application executes in the virtual machine; if it is an interactive application, a handle is provided back to the user (e.g. a login session, or a virtual display session such as VNC)
Conclusions
Classic virtual machines support a grid computing abstraction where computation becomes decoupled from the underlying physical resources. In this model, entire computing environments can be represented as data (a large state) and physical machines can be represented as resources for instantiating data. This abstraction is powerful because it decouples the administration of computing users from the administration of resource providers. This simplifies addressing many issues in grid computing and provides a new layer at which to work. We have presented a qualitative argument for the use of virtual machines in grid computing and quantitative results that demonstrate the feasibility of this idea from a performance perspective. We then illustrated the middleware challenges that must be overcome to build grid computing on top of virtual machine monitors and described how we are addressing those challenges. Finally, we provided a description of our nascent software architecture and its integration with existing middleware to support a VM-based infrastructure for computational grids. The envisioned architecture builds upon virtual machines, applications, data and networks from which necessary resources can be provided to the services layer.
Because zinc oxide is non-toxic and compatible with the body, the nano generators could be integrated into implantable biomedical devices to wirelessly measure blood flow and blood pressure within the body. They could also find moue ordinary applications in generating small current to power small body electronics. Finally, anything that makes the nanowires move within the generator can be used for generating power.
- WIRELESS CHARGING OF MOBILEPHONES USING MICROWAVES
With mobile phones becoming a basic part of life, the recharging of mobile phone batteries has always been a problem . The mobile phones vary in their talk time and battery stand by according to their manufacturer and batteries. All these phones irrespective of their manufacturer and batteries have to be put to recharge after the battery has drained out. The main objective of their manufacturer and battery make. In this paper a new proposal has been made so as to make the recharging of the mobile phones is done automatically as you talk in your mobile phone! This is done by use of microwaves. The microwave signal is transmitted from the transmitter along with the message signal using special kind of antennas called slotted wave guide antenna at a frequency is 2.45GHz. There are minimal additions, which have to be made in the mobile handsets, which are the addition of a sensor, a “rectenna” and a filter. With the above setup, the need for separate chargers for mobile phones is eliminated and makes charging universal . Thus the more you talk, the mobile phones is eliminated and makes charging universal. Thus the more you talk, the more is your mobile phone charged! With this proposal the manufacturers would be able to remove the talk time and battery stand by from their phone specifications!
INTRODUCTION
THE ELECTROMAGNETIC SPECTRUM
To start with, to know what a spectrum is: when white light is shone through a prism it is separated out into all the colours of the rainbow; this is the visible spectrum. So white light is a mixture of all colours. Black is NOT a colour; it is what you get when all the light is taken away.
Some physicists pretend that light consists of tiny particles which they call
photons. They travel at the speed of light (what a surprise). The speed of light is about
300,000,000 meters per second. When they hit something they might bounce off, go right
through or get absorbed. What happens depends a bit on how much energy they have. If
they bounce off something and then go into your eye you will "see" the thing they have
bounced off. Some things like glass and Perspex will let them go through; these materials
are transparent. Black objects absorb the photons so you should not be able to see black
things: you will have to think about this one. These poor old physicists get a little bit
confused when they try to explain why some photons go through a leaf, some are
reflected, and some are absorbed. They say that it is because they have different amounts
of energy.
Other physicists pretend that light is made of waves. These physicists measure the length of the waves and this helps them to explain what happens when light hits leaves. The light with the longest wavelength (red) is absorbed by the green stuff (chlorophyll) in the leaves. So is the light with the shortest wavelength (blue). In between these two colours there is green light, this is allowed to pass right through or is reflected. (Indigo and violet have shorter wavelengths than blue light.)
Well it is easy to explain some of the properties of light by pretending that it is made of tiny particles called photons and it is easy to explain other properties of light by pretending that it is some kind of wave.
The visible spectrum is just one small part of the electromagnetic spectrum. These electromagnetic waves are made up of two parts. The first part is an electric field. The second part is a magnetic field. So that is why they are called electromagnetic waves. The two fields are at right angles to each other.
THE MICROWAVE REGION
Microwave wavelengths range from approximately one millimeter (the thickness
of a pencil lead) to thirty centimeters (about twelve inches). In a microwave oven, the
radio waves generated are tuned to frequencies that can be absorbed by the food. The
food absorbs the energy and gets warmer. The dish holding the food doesn't absorb a
significant amount of energy and stays much cooler. Microwaves are emitted from the
Earth, from objects such as cars and planes, and from the atmosphere. These microwaves
can be detected to give information, such as the temperature of the object that emitted the
microwaves.
Microwaves have wavelengths that can be measured in centimeters! The longer
microwaves, those closer to a foot in length, are the waves which heat our food in a
microwave oven. Microwaves are good for transmitting information from one place to
another because microwave energy can penetrate haze, light rain and snow, clouds, and
smoke.
Shorter microwaves are used in remote sensing. These microwaves are used for radar like the Doppler radar used in weather forecasts. Microwaves, used for radar, are just a few inches long. Because microwaves can penetrate haze, light rain and snow, clouds and smoke, these waves are good for viewing the Earth from space
Microwave waves are used in the communication industry and in the kitchen as a way to cook foods. Microwave radiation is still associated with energy levels that are usually considered harmless except for people with pace makers.
Here we are going to use the S band of the Microwave Spectrum.
Microwave frequency bands
Designation Frequency range
L Band 1 to 2 GHz
S Band 2 to 4 GHz
C Band 4 to 8 GHz
X Band 8 to 12 GHz
Ku Band 12 to 18 GHz
K Band 18 to 26 GHz
Ka Band 26 to 40 GHz
Q Band 30 to 50 GHz
U Band 40 to 60 GHz
V Band 46 to 56 GHz
W Band 56 to 100 GHz
The frequency selection is another important aspect in transmission. Here we have selected the license free 2.45 GHz ISM band for our purpose.
The Industrial, Scientific and Medical (ISM) radio bands were originally reserved internationally for non-commercial use of RF electromagnetic fields for industrial, scientific and medical purposes.
The ISM bands are defined by the ITU-T in S5.138 and S5.150 of the Radio Regulations. Individual countries use of the bands designated in these sections may differ due to variations in national radio regulations.
In recent years they have also been used for license-free error-tolerant communications applications such as wireless LANs and Bluetooth:
900 MHz band (33.3 cm) ( also GSM communication in India )
2.45 GHz band (12.2 cm)
IEEE 802.11b wireless Ethernet also operates on the 2.45 GHz band
of a pencil lead) to thirty centimeters (about twelve inches). In a microwave oven, the
radio waves generated are tuned to frequencies that can be absorbed by the food. The
food absorbs the energy and gets warmer. The dish holding the food doesn't absorb a
significant amount of energy and stays much cooler. Microwaves are emitted from the
Earth, from objects such as cars and planes, and from the atmosphere. These microwaves
can be detected to give information, such as the temperature of the object that emitted the
microwaves.
Microwaves have wavelengths that can be measured in centimeters! The longer
microwaves, those closer to a foot in length, are the waves which heat our food in a
microwave oven. Microwaves are good for transmitting information from one place to
another because microwave energy can penetrate haze, light rain and snow, clouds, and
smoke.
Shorter microwaves are used in remote sensing. These microwaves are used for radar like the Doppler radar used in weather forecasts. Microwaves, used for radar, are just a few inches long. Because microwaves can penetrate haze, light rain and snow, clouds and smoke, these waves are good for viewing the Earth from space
Microwave waves are used in the communication industry and in the kitchen as a way to cook foods. Microwave radiation is still associated with energy levels that are usually considered harmless except for people with pace makers.
Here we are going to use the S band of the Microwave Spectrum.
Microwave frequency bands
Designation Frequency range
L Band 1 to 2 GHz
S Band 2 to 4 GHz
C Band 4 to 8 GHz
X Band 8 to 12 GHz
Ku Band 12 to 18 GHz
K Band 18 to 26 GHz
Ka Band 26 to 40 GHz
Q Band 30 to 50 GHz
U Band 40 to 60 GHz
V Band 46 to 56 GHz
W Band 56 to 100 GHz
The frequency selection is another important aspect in transmission. Here we have selected the license free 2.45 GHz ISM band for our purpose.
The Industrial, Scientific and Medical (ISM) radio bands were originally reserved internationally for non-commercial use of RF electromagnetic fields for industrial, scientific and medical purposes.
The ISM bands are defined by the ITU-T in S5.138 and S5.150 of the Radio Regulations. Individual countries use of the bands designated in these sections may differ due to variations in national radio regulations.
In recent years they have also been used for license-free error-tolerant communications applications such as wireless LANs and Bluetooth:
900 MHz band (33.3 cm) ( also GSM communication in India )
2.45 GHz band (12.2 cm)
IEEE 802.11b wireless Ethernet also operates on the 2.45 GHz band
TRANSMITTER DESIGN
The Magnetron
The MAGNETRON (A), is a self-contained microwave oscillator that operates differently from the linear-beam tubes, such as the TWT and the klystron. View (B) is a simplified drawing of the magnetron. CROSSED-ELECTRON and MAGNETIC fields are used in the magnetron to produce the high-power output required in radar and communications equipment.
The magnetron is classed as a diode because it has no grid. A magnetic field located in the space between the plate (anode) and the cathode serves as a grid. The plate of a magnetron does not have the same physical appearance as the plate of an ordinary electron tube. Since conventional inductive-capacitive (LC) networks become impractical at microwave frequencies, the plate is fabricated into a cylindrical copper block containing resonant cavities that serve as tuned circuits. The magnetron base differs considerably from the conventional tube base. The magnetron base is short in length and has large diameter leads that are carefully sealed into the tube and shielded.
The cathode and filament are at the center of the tube and are supported y
the filament leads. The filament leads are large and rigid enough to keep the
cathode and filament structure fixed in position. The output lead is usually a probe
or loop extending into one of the tuned cavities and coupled into a waveguide or
coaxial line. The plate structure, shown in figure 2 -18, is a solid block of copper.
The cylindrical holes around its circumference are resonant cavities. A narrow
slot runs from each cavity into the central portion of the tube dividing the inner
structure into as many segments as there are cavities
strapped together to put the cavities in parallel with regard to the output. The
cavities control the output frequency. The straps are circular, metal bands that are
placed across the top of the block at the entrance slots to the cavities. Since the
cathode must operate at high power, it must be fairly large and must also be able
to withstand high operating temperatures. It must also have good emission
characteristics, particularly under return bombardment by the electrons. This is
because most of the output power is provided by the large number of electrons
that are emitted when high-velocity electrons return to strike the cathode. The
cathode is indirectly heated and is constructed of a high-emission material. The
open space between the plate and the cathode is called the INTERACTION
SPACE. In this space the electric and magnetic fields interact to exert force upon
the electrons.
ABSTRACT
RECEIVER DESIGN
The basic addition to the mobile phone is going to be the rectenna.
A rectenna is a rectifying antenna, a special type of antenna that is used to directly convert microwave energy into DC electricity. Its elements are usually arranged in a mesh pattern, giving it a distinct appearance from most antennae.A simple rectenna can be constructed from a schottky diode placed between antenna dipoles. The diode rectifies the current induced in the antenna by the microwaves.
Rectennae are highly efficient at converting microwave energy to electricity. In laboratory environments, efficiencies above 90% have been observed with regularity. Some experimentation has been done with inverse rectennae, converting electricity into microwave energy, but efficiencies are much lower--only in the area of 1%.
With the advent of nanotechnology and MEMS the size of these devices can be
brought down to molecular level. It has been theorized that similar devices, scaled down
to the proportions used in nanotechnology, could be used to convert light into electricity
at much greater efficiencies than what is currently possible with solar cells. This type of
device is called an optical rectenna. Theoretically, high efficiencies can be maintained as
the device shrinks, but experiments funded by the United States National Renewable
Energy Laboratory have so far only obtained roughly 1% efficiency while using infrared
light.
Another important part of our receiver circuitry is a simple sensor. This is simply used to identify when the mobile phone user is talking. As our main objective is to charge the mobile phone with the transmitted microwave after rectifying it by the rectenna, the sensor plays an important role.
The whole setup looks something like this.
THE PROCESS OF RECTIFICATION
Studies on various microwave power rectifier configurations show that a bridge
configuration is better than a single diode one. But the dimensions and the cost of that
kind of solution do not meet our objective. This study consists in designing and
simulating a single diode power rectifier “in hybrid technology” with improved
sensitivity at low power levels. We achieved good matching between simulation results
and measurements thanks to the optimisation of the packaging of the Schottky diode.
Microwave energy transmitted from space to earth apparently has the potential to provide environmentally clean electric power on a very large scale. The key to improve transmission efficiency is the rectifying circuit. The aim of this study is to make a low cost power rectifier for low and high power levels at a frequency of 2.45 GHz with good efficiency of rectifying operation. The objective also is to increase the detection sensitivity at low levels of power.
Different configurations can be used to convert the electromagnetic wave into DC signal, the study done in showed that the use of a bridge is better than a single diode, but the purpose of this study is to achieve a low cost microwave rectifier with single Schottky diode for low and high power levels that has a good performances.
This study is divided on two kind of technologies the first is the hybrid technology and the second is the monolithic one.
The goal of this investigation is the development of a hybrid microwave rectifier with single Schottky diode. The first study of this circuit is based on the optimization of the rectifier in order to have a good matching of the input impedance at the desired frequency 2.45GHz. Besides, the aim of the second study is the increasing of the detection sensitivity at low levels of power.
SENSOR CIRCUITRY
The sensor circuitry is a simple circuit, which detects if the mobile phone receives any message signal. This is required, as the phone has to be charged as long as the user is talking. Thus a simple F to V converter would serve our purpose. In India the operating frequency of the mobile phone operators is generally 900MHz or 1800MHz for the GSM system for mobile communication. Thus the usage of simple F to V converters would act as switches to trigger the rectenna circuit to on.
A simple yet powerful F to V converter is LM2907. Using LM2907 would greatly serve our purpose. It acts as a switch for triggering the rectenna circuitry. The general block diagram for the LM2907 is given below.
Thus on the reception of the signal the sensor circuitry directs the rectenna circuit to ON and the mobile phone begins to charge using the microwave power.
CONCLUSION
Thus this paper successfully demonstrates a novel method of using the power of the microwave to charge the mobile phones without the use of wired chargers. Thus this method provides great advantage to the mobile phone users to carry their phones anywhere even if the place is devoid of facilities for charging. A novel use of the rectenna and a sensor in a mobile phone could provide a new dimension in the revelation of mobile phone.
The MAGNETRON (A), is a self-contained microwave oscillator that operates differently from the linear-beam tubes, such as the TWT and the klystron. View (B) is a simplified drawing of the magnetron. CROSSED-ELECTRON and MAGNETIC fields are used in the magnetron to produce the high-power output required in radar and communications equipment.
The magnetron is classed as a diode because it has no grid. A magnetic field located in the space between the plate (anode) and the cathode serves as a grid. The plate of a magnetron does not have the same physical appearance as the plate of an ordinary electron tube. Since conventional inductive-capacitive (LC) networks become impractical at microwave frequencies, the plate is fabricated into a cylindrical copper block containing resonant cavities that serve as tuned circuits. The magnetron base differs considerably from the conventional tube base. The magnetron base is short in length and has large diameter leads that are carefully sealed into the tube and shielded.
The cathode and filament are at the center of the tube and are supported y
the filament leads. The filament leads are large and rigid enough to keep the
cathode and filament structure fixed in position. The output lead is usually a probe
or loop extending into one of the tuned cavities and coupled into a waveguide or
coaxial line. The plate structure, shown in figure 2 -18, is a solid block of copper.
The cylindrical holes around its circumference are resonant cavities. A narrow
slot runs from each cavity into the central portion of the tube dividing the inner
structure into as many segments as there are cavities
strapped together to put the cavities in parallel with regard to the output. The
cavities control the output frequency. The straps are circular, metal bands that are
placed across the top of the block at the entrance slots to the cavities. Since the
cathode must operate at high power, it must be fairly large and must also be able
to withstand high operating temperatures. It must also have good emission
characteristics, particularly under return bombardment by the electrons. This is
because most of the output power is provided by the large number of electrons
that are emitted when high-velocity electrons return to strike the cathode. The
cathode is indirectly heated and is constructed of a high-emission material. The
open space between the plate and the cathode is called the INTERACTION
SPACE. In this space the electric and magnetic fields interact to exert force upon
the electrons.
ABSTRACT
RECEIVER DESIGN
The basic addition to the mobile phone is going to be the rectenna.
A rectenna is a rectifying antenna, a special type of antenna that is used to directly convert microwave energy into DC electricity. Its elements are usually arranged in a mesh pattern, giving it a distinct appearance from most antennae.A simple rectenna can be constructed from a schottky diode placed between antenna dipoles. The diode rectifies the current induced in the antenna by the microwaves.
Rectennae are highly efficient at converting microwave energy to electricity. In laboratory environments, efficiencies above 90% have been observed with regularity. Some experimentation has been done with inverse rectennae, converting electricity into microwave energy, but efficiencies are much lower--only in the area of 1%.
With the advent of nanotechnology and MEMS the size of these devices can be
brought down to molecular level. It has been theorized that similar devices, scaled down
to the proportions used in nanotechnology, could be used to convert light into electricity
at much greater efficiencies than what is currently possible with solar cells. This type of
device is called an optical rectenna. Theoretically, high efficiencies can be maintained as
the device shrinks, but experiments funded by the United States National Renewable
Energy Laboratory have so far only obtained roughly 1% efficiency while using infrared
light.
Another important part of our receiver circuitry is a simple sensor. This is simply used to identify when the mobile phone user is talking. As our main objective is to charge the mobile phone with the transmitted microwave after rectifying it by the rectenna, the sensor plays an important role.
The whole setup looks something like this.
THE PROCESS OF RECTIFICATION
Studies on various microwave power rectifier configurations show that a bridge
configuration is better than a single diode one. But the dimensions and the cost of that
kind of solution do not meet our objective. This study consists in designing and
simulating a single diode power rectifier “in hybrid technology” with improved
sensitivity at low power levels. We achieved good matching between simulation results
and measurements thanks to the optimisation of the packaging of the Schottky diode.
Microwave energy transmitted from space to earth apparently has the potential to provide environmentally clean electric power on a very large scale. The key to improve transmission efficiency is the rectifying circuit. The aim of this study is to make a low cost power rectifier for low and high power levels at a frequency of 2.45 GHz with good efficiency of rectifying operation. The objective also is to increase the detection sensitivity at low levels of power.
Different configurations can be used to convert the electromagnetic wave into DC signal, the study done in showed that the use of a bridge is better than a single diode, but the purpose of this study is to achieve a low cost microwave rectifier with single Schottky diode for low and high power levels that has a good performances.
This study is divided on two kind of technologies the first is the hybrid technology and the second is the monolithic one.
The goal of this investigation is the development of a hybrid microwave rectifier with single Schottky diode. The first study of this circuit is based on the optimization of the rectifier in order to have a good matching of the input impedance at the desired frequency 2.45GHz. Besides, the aim of the second study is the increasing of the detection sensitivity at low levels of power.
SENSOR CIRCUITRY
The sensor circuitry is a simple circuit, which detects if the mobile phone receives any message signal. This is required, as the phone has to be charged as long as the user is talking. Thus a simple F to V converter would serve our purpose. In India the operating frequency of the mobile phone operators is generally 900MHz or 1800MHz for the GSM system for mobile communication. Thus the usage of simple F to V converters would act as switches to trigger the rectenna circuit to on.
A simple yet powerful F to V converter is LM2907. Using LM2907 would greatly serve our purpose. It acts as a switch for triggering the rectenna circuitry. The general block diagram for the LM2907 is given below.
Thus on the reception of the signal the sensor circuitry directs the rectenna circuit to ON and the mobile phone begins to charge using the microwave power.
CONCLUSION
Thus this paper successfully demonstrates a novel method of using the power of the microwave to charge the mobile phones without the use of wired chargers. Thus this method provides great advantage to the mobile phone users to carry their phones anywhere even if the place is devoid of facilities for charging. A novel use of the rectenna and a sensor in a mobile phone could provide a new dimension in the revelation of mobile phone.
- Advanced grid computing
Abstract
With the furtherance of technology, life is becoming simpler and less demanding. The conglomeration of three major disciplines, Computers, Communications and Electronics unleashes a vast amount of power in terms of technology. In an era of cost-cutting ,when companies are faced with a growing need to maximize and/or improve efficiencies of existing IT investments, organizations are turning to Grid Computing as a strategic solution.
This paper seeks to introduce this Grid Computing as an emerging computing model that provides the ability to perform higher throughput computing by taking advantage of many networked computers to model virtual computer architecture.
Further, it enumerates on how the Grids use the resources of many separate computers connected through a network to solve large-scale computation problems. It explains how the Grids provide the ability to perform computations on large data sets, by breaking them down into many smaller ones, or provide the ability to perform many more computations at once than would be possible on a single computer, by modeling a parallel division of labor between processes.
Finally the paper puts forth the Future of Grid Computing with a case-study and enlightens on how organizations can optimize computing and data resources, pool them for large capacity workloads, share them across networks and enable collaboration.
1.Introduction
Grid computing can mean different things to different individuals. The grand vision is often presented as an analogy to power grids where users (or electrical appliances) get access to electricity through wall sockets with no care or consideration for where or how the electricity is actually generated. In this view of grid computing, computing becomes pervasive and individual users (or client applications) gain access to computing resources (processors, storage, data, applications, and so on) as needed with little or no knowledge of where those resources are located or what the underlying technologies, hardware, operating system, and so on are.
With grid computing, an organization can transform its distributed and difficult-to-manage systems into a large virtual computer that can be set loose on problems and processes too complex for a single computer to handle efficiently. The problems to be solved can involve data processing, network bandwidth, or data storage. The systems linked in a grid might be in the same room or distributed around the world. They might be running different operating systems on many hardware platforms. They might even be owned by different organizations. Regardless of the depth of a grid's resources, the entire grid user experiences the processing resources of a very large virtual computer.
2.Definition of Grid Computing
With grid computing, an organization can transform its distributed and difficult-to-manage systems into a large virtual computer that can be set loose on problems and processes too complex for a single computer to handle efficiently. The problems to be solved can involve data processing, network bandwidth, or data storage. The systems linked in a grid might be in the same room or distributed around the world. They might be running different operating systems on many hardware platforms. They might even be owned by different organizations. Regardless of the depth of a grid's resources, the entire grid user experiences the processing resources of a very large virtual computer.
2.Definition of Grid Computing
Because it is an emerging technology, grid computing can mean different things to different people.
“Grid computing allows you to unite pools of servers, storage systems, and networks into a single large system so that you can deliver the power of multiple-systems resources to a single user point for a specific purpose.” To a user, data file, or an application, the system appears to be a single enormous virtual computing system.
3.Grid Network
3.1 A Simple Grid Network:
Illusion of a Virtual Computing Environment
Grid computing is the next logical step in distributed networking. A simple Grid Network contains a Grid Software which acts as an interface between any user (normal user, administrator) and the virtual computing environment (a superset of PC’s, Workstations, Super Computers).
3.2 Components of Grid Network:
Clusters, Workstations, Desktop PC’s, Super Computers contribute to the components of a grid. Each component might be an important component of a grid, but by itself doesn’t constitute a grid.
4.Evolution of GridIn fact, grid can be seen as the latest and most complete evolution of more familiar developments — such as distributed computing, the Web, peer-to-peer computing and virtualization technologies.
4.1 The Time Is Right:Many organizations feel that this is the right time to encourage Grid Computing for the following reasons:
- Unprecedented pressure to lower costs
- Inexpensive, commodity blade servers
- Inexpensive OS optimized for1-4CPUs
- Storage no longer tied to a single server
5.Functions
When you deploy a grid, it will be to meet a set of customer requirements. To better match grid computing capabilities to those requirements, it is useful to keep in mind the reasons for using grid computing. This section describes the most important capabilities of grid computing.
5.1 Optimal usage of resources:
Remote Applicability: The easiest use of grid computing is to run an existing application on a different machine.
Utility of un-used disk drive: Grid computing can be used to aggregate the unused storage into a much larger virtual data store.
Resource Utilization: Many resources such as CPU, Storage and so on, can be used with the principle of optimality.
5.2. Parallel CPU capacity:A CPU intensive grid application can be thought of as many smaller “sub jobs,” each executing on a different machine in the grid. For example, a job finishes 10 times faster if it uses 10 times the number of processors.
5.3 Virtual resources and virtual organizations for Collaboration:
In the past, distributed computing promised collaboration among a wider audience, and achieved it to some extent. Grid computing can take these capabilities to an even wider audience, while offering important standards that enable very heterogeneous systems to work together to form the image of a large virtual computing system offering a variety of resources.
5.4 Access to additional resources:
In addition to CPU and storage resources, a grid can provide access to other resources in additional numbers and/or capacity.
5.5 Resource balancing:
For applications that are grid-enabled, the grid can offer a resource balancing effect by scheduling grid jobs on machines with low utilization. Without a grid infrastructure, balancing decisions are difficult to prioritize and execute.
5.6 Reliability And Management:As there are various supplementary resources available for each resource, reliability is achieved to a greater extent.
The Grid software itself takes care of all the management among the various Grid components.
6.Grid Architecture
6.1 Layers of Grid Architecture:
• Fabric Layer: It provides access to some shared resources using Grid Protocols. Shared Resources can be computational resources, storage systems, catalogs, network resources, and sensors.
• Connectivity Layer: It defines the core communication and authentication protocols required for grid-specific network functions.
• Resources Layer: It defines protocols for secure negotiations, initiation and monitoring the control of sharing operations on individual resources. Information and management protocols define this layer.
• Collective Layer: It contains protocols and services that capture interactions among a collection of resources.
• Application Layer: User applications operate in this layer by using the services of other layers.
6.2 Grid Topology:
Intra grid:A typical intra grid topology exists within a single organization. The primary characteristics of an intra grid are a single security provider, bandwidth on the private network is high and always available, and there is a single environment within a single network.
Extra grid:Based on a single organization, the extra grid expands on the concept by bringing together two or more intra grids. An extra grid, typically involves more than one security provider, and the level of management complexity increases. The primary characteristics of an extra grid are dispersed security, multiple organizations, and WAN connectivity.
Inter grid:The primary characteristics of an inter grid include dispersed security, multiple organizations, and WAN connectivity. The data in an inter grid is global public data, and applications must be modified for a global audience.
6.3 Grid Software:
There are many aspects to grid computing that typically are controlled through software. These functions can be handled across a spectrum of very manual procedures to processes being handled through sophisticated software.
Donor software
Management Software
Communications Software
Schedulers Software
7.Grid Security
In a grid, the member machines are configured to execute programs rather than moving data. This makes an unsecured grid potentially fertile ground for viruses and Trojan horse programs. For this reason, it is important to understand which components of the grid must be rigorously secured. The high level grid security requirements are:
Authorization
Privacy
Confidentiality
Manageability
Firewall
8.Case Study
Task: To Find the Annual Income of all the employees of an organization that is wide spread through out the world.
Assignment: This task is assigned to a processor of a grid.
Assignment: This task is assigned to a processor of a grid.
Work-Flow:
• This processor initially checks if the task is too large for a single processor to handle.
• If so, distributes the task among various devices of the grid, here comes the aspect of Parallel CPU Capacity. The processors job is to collect the Incoming data files and this is simply done through WAN/Internet.
• The Annual Incomes of the employees starts getting accumulated in the disk drive of the processor. Once there is no more disk space left with it, it has a privilege of using the storage device that has been idle for the past few hours in the same grid network; the functional Application Exploiting under Utilized Resources is taken advantage of at this point.
• Suppose a high priority task has been assigned to this device, it has a capability to transfer the relatively low priority task to some other device of the network and can finish its high priority task as per the dead line, thereby Utilizing Resources.
9.Conclusion
It is important to know that grid is not a silver bullet that can take any application and run it a 1000 times faster without the need for buying any more machines or software. Grid computing appears to be a promising trend for three reasons:
(1) Its ability to make more cost-effective use of a given amount of computer resources.
(2) As a way to solve problems that can't be approached without an enormous amount of computing power.
(3) Because it suggests that the resources of many computers can be cooperatively and perhaps synergistically harnessed and managed as collaboration towards a common objective.
GRID COMPUTING ON VIRTUAL MACHINES
Abstract
We advocate a novel approach to grid computing that is based on a combination of classic” operating system level virtual machines (VMs) and middleware mechanisms to manage VMs in a distributed environment. The abstraction is that of dynamically instantiated and mobile VMs that are a combination of traditional OS processes (the VM monitors) and files (the VM state). We give qualitative arguments that justify our approach in terms of security, isolation, customization, legacy support and resource control, and we show quantitative results that demonstrate the feasibility of our approach from a performance perspective. Finally, we describe the middleware challenges implied by the approach and architecture for grid computing using virtual machines.
Introduction
The fundamental goal of grid computing is to seamlessly multiplex distributed computational resources of providers among users across wide area networks. In traditional computing environments, resources are multiplexed using the mechanisms found in typical operating systems. For instance, user accounts and time-sharing enable the multiplexing of processors, virtual memory enables the multiplexing of main memory, and file systems multiplex disk storage. These and other traditional multiplexing mechanisms assume that trust and accountability are established by a centralized administration entity. In contrast, multiplexing in a grid environment must span independent administrative domains, and cannot rely on a central authority. The level of abstraction upon which current grid middleware solutions are implemented is that of an operating system user. This approach suffers from the limitations of traditional user account models in crossing administrative domain boundaries. In practice, multiplexing at this level of abstraction makes it difficult to implement the security mechanisms that are necessary to protect the integrity of grid resources from untrusted, legacy codes run on general purpose operating systems by untrusted users. It also greatly complicates the management of accounts and file systems that are not suited for wide-area environments. Unfortunately, most applications need precisely these services. Virtual machines present the image of a dedicated raw machine to each user. This abstraction is very powerful for grid computing because users then become strongly decoupled from
a) the system software of the underlying resource, and
b) other users sharing the resource.
In terms of security, VMs ensure that an untrusted user or application can only compromise their own operating system within a virtual machine, not the computational resource (nor other VMs). In terms of administration, virtual machines allow the configuration of an entire operating system to be independent from that of the computational resource; it is possible to completely represent a VM “guest” machine by its virtual state (e.g. stored in a conventional file) and instantiate it in any VM “host”, independently of the location or the software configuration of the host.
Why Grid Computing with Classic VMs?
The high-level answer to this question is that classic virtual machines provide a new abstraction layer, with low overhead that offers functionality that greatly simplifies addressing many of the issues of grid computing.
Introduction
The fundamental goal of grid computing is to seamlessly multiplex distributed computational resources of providers among users across wide area networks. In traditional computing environments, resources are multiplexed using the mechanisms found in typical operating systems. For instance, user accounts and time-sharing enable the multiplexing of processors, virtual memory enables the multiplexing of main memory, and file systems multiplex disk storage. These and other traditional multiplexing mechanisms assume that trust and accountability are established by a centralized administration entity. In contrast, multiplexing in a grid environment must span independent administrative domains, and cannot rely on a central authority. The level of abstraction upon which current grid middleware solutions are implemented is that of an operating system user. This approach suffers from the limitations of traditional user account models in crossing administrative domain boundaries. In practice, multiplexing at this level of abstraction makes it difficult to implement the security mechanisms that are necessary to protect the integrity of grid resources from untrusted, legacy codes run on general purpose operating systems by untrusted users. It also greatly complicates the management of accounts and file systems that are not suited for wide-area environments. Unfortunately, most applications need precisely these services. Virtual machines present the image of a dedicated raw machine to each user. This abstraction is very powerful for grid computing because users then become strongly decoupled from
a) the system software of the underlying resource, and
b) other users sharing the resource.
In terms of security, VMs ensure that an untrusted user or application can only compromise their own operating system within a virtual machine, not the computational resource (nor other VMs). In terms of administration, virtual machines allow the configuration of an entire operating system to be independent from that of the computational resource; it is possible to completely represent a VM “guest” machine by its virtual state (e.g. stored in a conventional file) and instantiate it in any VM “host”, independently of the location or the software configuration of the host.
Why Grid Computing with Classic VMs?
The high-level answer to this question is that classic virtual machines provide a new abstraction layer, with low overhead that offers functionality that greatly simplifies addressing many of the issues of grid computing.
Definitions
A modern operating system uses multiprogramming, virtual memory, and file systems to share CPU, memory, and disk resources among multiple processes and users. Each process accesses the physical resources indirectly, through abstractions provided by the operating system. Contemporaneous to the development of these mechanisms was that of another resource-sharing approach, virtual machines. A virtual machine presents the view of a duplicate of the underlying physical machine to the software that runs within it, allowing multiple operating systems to run concurrently and multiplex resources of a computer - processor, memory, disk, and network. Virtual machines can be divided into two main categories: those that virtualize a complete instruction set architecture (ISA-VMs) including both user and system instructions, and those that support an application binary interface (ABI-VMs) with virtualization of system calls. An important class of virtual machines (“classic” VMs) consists of ISA-VMs that support same-ISA execution of entire operating systems. A classic virtual machine abstraction allows for great flexibility in supporting multiple operating systems and is the focus of this paper.
Advantages
Unlike conventional operating systems, classic VMs allow dynamic multiplexing of users onto physical resources at the granularity of a single user per operating system session, thereby supporting per-user VMconfiguration and isolation from other users sharing the same physical resource. In the remainder of this section we focus on a scenario where each dynamic instance of a classic VM is dedicated to a single logical user.
1. Security and isolation
2. Customization
3. Administrator privileges
4. Resource control
5. Performance considerations
The advantages of virtual machines are for naught if they can not deliver sufficient performance. Virtual machine monitors incur performance overheads when applications within a VM execute privileged instructions that must be trapped and emulated. These are typically issued by kernel code of “guest” VMs during system calls, virtual memory handling, context switches and I/O. User-level code within VMMs runs directly on hardware without translation overheads. The overall overhead incurred by VMs thus depends on system characteristics, including the processor’s ISA, the VMM architecture and implementation, and the type of workload running in the system.
Table 1. Macrobenchmark results. User, system and total times are reported for three scenarios: physical machine, VM with state in local disk, VM with state accessed via NFS-based grid virtual file system (PVFS). Overheads are calculated using execution times and the physical machine as reference. In the PVFS scenario, the physical and data servers are located at Northwestern University, while the image server is located at the University of Florida.
Figure 1. Microbenchmark results: slowdown of synthetic test task under presence of background load for twelve different scenarios.
Table 2. Average, standard deviation, minimum and maximum VM startup times. Virtual machine sessions are instantiated using globusrun (Globus 2.0 toolkit) within a LAN. Measurements have been taken across 10 samples. Time (in seconds) is measured as wall-clock execution time from the beginning to the end of the execution of globusrun.
Middleware challenges
1. Data management
Data management is a key technology for VM-based grid computing, enabling administrative decoupling of computation providers and users. Data management involves: the transfer of VM images so that a user’s virtual machine can be instantiated anywhere and migrated when necessary, and support for location-independent access to user files. With appropriate data management support, computation, state, and user data can reside in different domains.
The components of a virtual machine session are distributed across three different logical entities: image servers, which provide the capability of archiving static VM states; computation servers (or VM hosts), which provide the capability of instantiating dynamic VM images (or VM guests); and data servers, which provide the capability of storing user data. In this scenario, VM state information needs to be transferred from an image server to a VM host (where it is instantiated), and from a data server to the VM guest (where it is processed) as in Figure 2.
High performance data transfers: Fast and simple access to images and user data is critical. Current grid solutions, such as Globus [4, 1] and PBS [3] typically employ file-staging techniques to transfer files between user accounts in the absence of a common file system.
Figure 3. Architecture for a VM-based grid service. In 1- 6, a virtual machine (V4) is dynamically created by middleware front-end F on behalf of user X. This VM is dedicated to a single user. In another scenario, virtual machines V1, V2 are instantiated on P2 on behalf of a service provider S, and are multiplexed across users A, B, C and applications provided by S. The logical user account abstraction decouples access to physical resources (middleware) from access to virtual resources (end-users and services).
In the following we lay out initial software architecture for virtual machine grid computing by describing the life cycle of a VM within it.
1. A user X (or grid middleware F on their behalf) first consults an information service, querying for a VM future (a physical machine able to instantiate a dynamic VM) P that meets their needs.
2. If necessary, X also consults an information service to query for a VM image server I with a base O/S installation that meets their application needs. Alternatively, users may provide VM images of their own (e.g. a customized O/S installation).
3. The middleware then establishes a data session between the physical server P and the image server I to allow for the instantiation of a dynamic VM. This data connection can be established via explicit transfers (e.g. Grid FTP) or via implicit, on-demand transfers (e.g. a grid virtual file system, Figure 2).
4. Once the data session for image I is established, the user can negotiate with the physical machine the startup of a VM instance Vi (e.g. using Globus GRAM or SSH). The virtual machine Vi may start from a preboot (cold) state, or from a post-boot (warm) state stored as part of the image. In addition, upon startup, the VM is assigned an IP address (via DHCP, or by connecting to a virtual network).
5. Once the VM instance Vi is running and on the network, additional data sessions are established. These connect the O/S within Vi to application server A and to the user’s data server D. As previously, these sessions can be realized with explicit or implicit transfers (Figure 2).
6. The application executes in the virtual machine; if it is an interactive application, a handle is provided back to the user (e.g. a login session, or a virtual display session such as VNC)
Conclusions
Classic virtual machines support a grid computing abstraction where computation becomes decoupled from the underlying physical resources. In this model, entire computing environments can be represented as data (a large state) and physical machines can be represented as resources for instantiating data. This abstraction is powerful because it decouples the administration of computing users from the administration of resource providers. This simplifies addressing many issues in grid computing and provides a new layer at which to work. We have presented a qualitative argument for the use of virtual machines in grid computing and quantitative results that demonstrate the feasibility of this idea from a performance perspective. We then illustrated the middleware challenges that must be overcome to build grid computing on top of virtual machine monitors and described how we are addressing those challenges. Finally, we provided a description of our nascent software architecture and its integration with existing middleware to support a VM-based infrastructure for computational grids. The envisioned architecture builds upon virtual machines, applications, data and networks from which necessary resources can be provided to the services layer.
- ROLE OF GRID COMPUTING
ABSTRACT
In recent years, numerous organizations have been vying for donated resources for their grid applications. Potential resource donors are inundated with worth- while grid projects such as discovering a cure for AIDS, finding large prime numbers, and searching for extraterrestrial intelligence. We believe that fundamental to the establishment of a grid computing framework where all (not just large organizations) are able to effectively tap into the resources available on the global network is the establishment of trust between grid application developers and resource donors. Resource donors must be able to trust that their security, safety, and privacy policies will be respected by programs that use their systems.
The purpose of this seminar to give the basic overview of Grid computing, in such way that reader will able to understand basic concept of grid computing, principal operation and some of the issues of Grid computing.
Grid computing enables the use and pooling of computer and data resources to solve complex mathematical problems. The technique is the latest development in an evolution that earlier brought forth such advances as distributed computing, the Worldwide Web, and collaborative computing.
GRID COMPUTING:-
Grid computing is form of networking unlike conventional network that focus on communications among devices. It harnesses unused processing cycles of all computers in a network for solving problems too intensive for any stand-alone machine.
Grid computing is a method of harnessing the power of many computers in network to solve problems requiring a large numbers of processing cycles and involving huge amount of data in grid computing pcs, servers and workstations are linked together so that computing capacity is never wasted.
So rather than using a network of computers simply to communicate and transfer data, grid computing taps the unused processor cycles or numerous i.e thousands of computers. It is distributed computing taken to the next evolutionary level .The goal of grid computing is to create the illusion of a simple yet large and powerful self managing virtual computer out of large collection of connected heterogeneous system sharing various combination of resources grid . Computing is a way to enlist large no of machines to work on multipart computational problem such as circuit analysis or mechanical design. It harnesses a diverse array of machines and other resources to rapidelly. Process to solve problem beyond an organization's available capacity. Once a proper infrastructure is in place, a user will have access to a virtual computer that is reliable and adaptable to the users, for this, there must be standard for grid computing that will allow a secure and robust infrastructure to be built. Standards such as Open Grid Services Architecture (OGSA) and tools such as provided by Globus Toolkit provide the necessary framework. Grid computing uses open source protocol and software called Globus. Globus software allows computes to share data, power and software.
BASIC CONCEPT OF GRID COMPUTING
HOW IT WORKS?
The computer is tied to network such as internet, which enables regular people with home pcs to participate in the grid project from anywhere in the world. The pc owners have to download simple software from the projects host site. And the project sites use the software that can divide and distribute the pises of program to thousands of computers for processing. The above system shows a grid computing system that is distributed among the various local domains.
Working:
A grid user have to installed the provided grid s/w on his m/c .m/c is connected with Internet. Internet is most far reaching n/w. The user establishes his identity with a certificate authority. The user has responsibility of keeping his grid secure. Once the user and/or machine are authenticated, the grid software provided to the user for installing on his machine for the purposes of using the grid as well as donating to the grid. This software may be automatically reconfigured by the grid management system to know the communication address of the management nodes in the grid and user or machine identification information. In this way, the installation may be a one click operation. To use the grid, most grid systems require the user to log on to a system using a user ID that is enrolled in the grid. Once logged on, the user can query the grid and submit jobs. The user will usually perform some queries to check to see how busy the grid is, to see how his submitted jobs are progressing, and to look for resources on the grid. Grid systems usually provide command line tools as well as graphical user interfaces (GUIs) for queries. Command line tools are especially useful when the user wants to write a script.
Job submission usually consists of three parts, even if there is only one command required. First, some input data and possibly the executable program or execution script file are sent to the machine to execute the job. Sending the input is called “staging the input data.” Second, the job is executed on the grid machine. The grid software running on the donating machine executes the program in a process on the user’s behalf. Third, the results of the job are sent back to the submitter. When there are a large number of sub jobs, the work required to collect the results and produce the final result is usually accomplished by a single program, usually running on the machine at the point of job submission. The data accessed by the grid jobs may simply be staged in and out by the grid system. Depending on size and no.of jobs, this can be added up to a large amount of data traffic. The user can query the grid system to see how his application and its sub jobs are Progressing.
A job may fail due to a:
1. Programming error: The job stops part way with some program fault.
2. Hardware or power failure: The machine or devices being used stop Working in some way.
3. Communications interruption: A communication path to the machine has
Failed or is overloaded with other data traffic.
3. Excessive slowness: The job might be in an infinite loop or normal job
Progress may be limited by another process running at a higher priority or some other form of contention. Grid applications can be designed to automate the monitoring and recovery of their own sub jobs using functions provided by the grid system software application programming interfaces (APIs).
Grid computing harnesses a diverse array of machines and other resources to rapidly process and solve problems beyond an organization’s available capacity. Academic and government researchers have used it for several years to solve large-scale problems, and the private sector is increasingly adopting the technology. To create innovative products and services, reduce time to market, and enhance Business processes.
Fig .1.Aset of methods describes the connectivity of the original problem cell (opc)
APPLICATION OF GRID COMPUTING:
The grid computing is used to solve the problems which are beyond the scope of single processor, the problems involving the large amount of computations or the analysis of huge amount of data. Right now there are scientific and technical projects such as cancer and other medical research projects that involve the analysis of the inordinate amount of data. Now a days grid computing is used by the sites which are the hosts o the large online games. There are many users on the Internet playing a large online game; there is information of the virtual organization of all the players. Grids are primarily being used today by universities and research lab for project that require high performance computing applications. These projects require a large amount of computer processing power or access to large amount of data.
TYPES OF GRID:-
COMUTATION GRID:
A computational grid is focused on settings aside resources specifically for computing power .In this type of grid most of machines are high performance servers.
SCAVENGING GRID:
A scavenging grid is most commonly used with large numbers of desktop machines. Machines are scavenged for available CPU cycles and other resources.
Owners of desktop machines are usually given control over when their resources are available to participate in the grid.
DATA GRID:
A data grid is responsible for housing and providing access to data across multiple organizations. Users are not concerned with where this data is located as long as they access to the data .A data grid allow to share data, manage the data and manage security.
GLOBUS PROJECT:The Globus project is a joint effort on the part of researchers and developers from around the word that are focused on the concept of grid computing its organized around four main activities:-
1. Research
2. Software tools
3. Test beds
4. Applications
BENEFITS OF GRID COMPUTING
BUSSINESS BENEFITS:
ACCELERATE TIME TO RESULT
• Accelerate time to results:
• Can help improve productivity and collaboration.
• Can help solve problems that were previously unsolvable.
ENABLE COLLABORATION AND PROMOTE OPERATIONAL FLEXIBILITY• Bring together not only IT resources but also people.
• How widely dispersed departments and businesses to create virtual
• Organizations to share data and resources.
EFFICIENTLY SCALE TO MEET VARIABLE BUSINESS DEMANDS
• Create flexible, resilient operational infrastructures.
• Address rapid fluctuations in customer demands needs.
• Instantaneously access compute and data resources to "sense and Respond" to Needs.
INCREASE PRODUCTIVITY:
• Can help give end-users uninhibited access to the computing, data and storage resources they need (when they need them) .
• Can help equip employees to move easily through product dies phases, research Projects and faster than ever.
• Can help you improve optimal utilization of computing capabilities.
• Can help you avoid common pitfalls of over-provisioning and incurring excess costs.
• Can free IT organizations from the burden of administering disparate, Non-integrated systems.
TECHNOLOGY BENIFITS:-
INFRASTRUCTURE OPTIMIZATION:
• Consolidate workload management.
• Reduce cycle times.
INCREASE ACCESS TO DATA AND COLLABORATION:
• Federate data and distribute it globally.
• Support large multi-disciplinary collaboration..
• Enable collaboration across organizations and among businesses.
RESILIENT, HIGHLY AVAILABLE INFRASTRUCTURE:
• Balance work loads.
• Foster business community
• Enable recovery and failure.
CAPABILITY OF GRID COMPUTING:
1. EXPLOITING UNDERUTILIZED RESOURCES:The easiest use of grid computing is to run an existing application on a different machine. The processing resources are not the only ones that may be underutilized. Often, machines may have enormous unused disk drive capacity. Grid computing, more specifically, a data can be used to aggregate this unused storage into a much larger virtual data store, possibly configured to achieve improved performance and reliability over that of any single another function of the grid is to better balance resource utilization.
2. VIRTUAL RESOURCES AND VIRTUAL ORGANIZATION FOR COLLABORATION:
Another important grid computing contribution is to enable and simplify collaboration among a wider audience. Grid computing takes these capabilities to an even wider audience, while offering important standards that enable very heterogeneous systems to work together to form the image of a large virtual computing system offering a variety of virtual resources, The users of the grid can be organized dynamically into a number of virtual organizations, each with different policy requirements. These virtual organizations can share their resources collectively as a larger grid.
3. ACCESS TO ADDITIONAL RESOURCES:
In addition to CPU and storage resources, a grid can provide access to increased quantities of other resources and to special equipment, software, licenses, and other services. The additional resources can be provided in additional numbers and/or capacity.
4. RESOURCE BALANCING:
A grid federates a large number of resources contributed by individual machines into a greater total virtual resource. For applications that are grid enabled, the grid can offer a resource balancing effect by scheduling grid jobs on machines with low utilization. This feature can prove invaluable for handling occasional peak loads of activity in parts of a larger organization. This can happen in two ways: An unexpected peak can be routed to relatively idle machines in the grid. If the grid is already fully utilized, the lowest priority work being performed on the grid can be temporarily suspended or even cancelled and performed again later to make room for the higher priority work.
Without a grid infrastructure, such balancing decisions are difficult to prioritize and execute.
5. MANAGEMENT:
The goal to virtualize the resources on the grid and more uniformly handle heterogeneous systems will create new opportunities to better manage a larger, more disperse IT infrastructure. It will be easier to visualize capacity and utilization, making it easier for IT departments to control expenditures computing resources over a larger organization. The grid offers management of priorities among different projects.
USING A GRID: AN APPLICATION DEVELOPERS PERSPECTIVE:
Grid applications can be categorized in one of the following three categories:
Application that are not enabled for using multiple processors but can be executed on different machines.
Applications that are already designed to use the multiple processors of a grid setting.
Applications that need to be modified or rewritten to better exploit grid.
- EVOLUTION IN GRID COMPUTING
GRID COMPUTING
CONTENTS:
CONTENTS:
1. ABSTRACT
2. INTRODUCTION TO COMPUTING
3. TYPES OF GRID COMPUTING
4. ISSUES
5. APPLICATIONS
6. A SIMPLE HELLO WORLD EXAMPLE
7. DOWNSIDESOF GRID COMPUTING
8. CONCLUSION
1: ABSTRACT:
Grid computing is said to be the next big thing in IT. Research in grid computing is making rapid progress, owing to the increasing need for large-scale computation in the resolution of complex problems.
Clusters are, in a sense, the predecessors of grid technology. Clusters interconnect nodes through a local high-speed network, using commodity hardware, with the aim of reducing the costs of such infrastructures.
Supercomputers have been replaced by clusters of workstations in a large number of research projects.
Grids provide access to widely distributed computing and data resources, allowing data-intensive applications significantly improved data access, management and analysis. Nowadays there are a huge number of data intensive applications in several domains such as physics, climate modeling, biology/bio-informatics, addressing some of the most important current problems.
Computing grids are conceptually not unlike electrical grids. When you connect to the electrical grid, you don’t need to know where the power plant is or how the current gets to you. Grid computing uses middleware to coordinate disparate IT resources across a network, allowing them to function as a virtual whole.
Grids use a layer of middleware to communicate with and manipulate heterogeneous hardware and data sets. In some fields— astronomy, for example—hardware cannot reasonably be moved and is prohibitively expensive to replicate on other sites.
Grids address two distinct but related goals: providing remote access to IT assets, and aggregating processing power. The most obvious resource included in a grid is a processor, but grids also encompass sensors, data-storage systems, applications, and other resources.
Grids use a layer of middleware to communicate with and manipulate heterogeneous hardware and data sets. In some fields— astronomy, for example—hardware cannot reasonably be moved and is prohibitively expensive to replicate on other sites.
Many grids are appearing in the sciences, in fields such as chemistry, physics, and genetics, and cryptologists and mathematicians have also begun working with grid computing. Grid technology has the potential to significant impact other areas of study with heavy computational requirements, such as urban planning. Another important area for the technology is animation, which requires massive amounts of computational power and is a common tool in a growing number of disciplines included in a grid is a processor, but grids also encompass sensors, data-storage systems, applications, and other resources.
2: INTRODUCTION
TO COMPUTING:
Grid computing is an implementation in an enterprise computing taxonomy .It consists of family of technologies for opportunistically providing computing power from a pool of resources. Grid computing is opportunistic since it has to wait for resources to become available. The resources may include computing cycles, file and data storage, caching, network bandwidth, databases and application software. These resources can be distributed diversely on the globe .Provision of computer power means the methods and mechanisms for locating, authorizing, assembling, scheduling, releasing and accounting for resources and their usage.
For example compute grids share computational and data resources. And some grids share both and can also share network bandwidth, storage and caching resources and application software.
So the first dimension reflects the types of resources that the grid can use .Second dimension describes a grids geographic or administrative reach .Third dimension tells how the companies can get the resources. Fourth dimension reflects the partnerships between the Enterprises. The Fifth dimension reflects for what type of application a grid is used for biology, sensors or any other access.
So this proves that a Grid is multidimensional.
Coming to the Cluster, they are connected commonly connected to a high speed LANS. Clusters are usually deployed to improve speed and/or reliability over that provided by a single computer, while typically being much more cost-effective than single computers of comparable speed or reliability. They can be geographically distributed, but are often closely coupled in the same room.
Clusters can consist of heterogeneous processors and peripherals but they are homogeneous and use high performance and special purpose interconnection networks.
Fig: clusters in a university
But a CLUSTER is not a grid.
Since Computer Clusters require a much higher degree of centralized control, this point clearly distinguishes between a cluster and a grid.
Mainly the grid community focuses on issues such as Reliability, Security, Service and Quality Performance and Resource integration.
3:TYPES OF GRID COMPUTING:
1: Utility Computing:
Here, the main idea is to offer computing resources as an on-demand service to customers in much the same way that utilities offer electrical, gas, water, and telephone services to households and businesses. The utility computing service provider offers hosted computing resources.
One distinction is that the on-demand computing resources can comprise a grid in the service provider’s realm, and the grid can span several sites in the provider’s service area. Grid economies and scalability add a new dimension.
2: Autonomic computing:
Autonomic computing architectures monitor utilization and performance, tune and manage themselves, and adapt to failure. Some share resources and schedule tasks with other systems. The fundamental components of an autonomic computing system provide functions that computing grids will almost certainly need to operate effectively, such as the ability to recover lost computational subtasks.
As grids evolve, they might take on many of the characteristics of an autonomic computing system: Self-monitoring, diagnosis, and adaptability in their youth; sophisticated resource scheduling and forecasting; and perhaps a vertebrate-like involuntary autonomic nervous system at maturity. So the real issue is the extent to which a grid has adopted the characteristics of autonomic computing.
3: Peer-to-peer computing:
Peer-to-peer computing is one type of application that uses grid services to advertise, find, and share files.
The grid community tends to focus on top-down issues such as
1: resource integration,
2: performance,
3: reliability,
4: service quality, and
5: security.
The peer-to-peer community tends to focus on bottom up issues such as narrowly defined and specialized services, and support for tens of thousands of concurrent participants.
4: ISSUES:
The success of grid computing depends on fundamental issues in 2 main areas:
1: security
2: performance
Security:
Grids must deal with every security that any enterprise-owned or outsourced computing model faces. Security issues include secure authentication, access rights and privileges. Reliable and secure communications, perhaps with encryption, are also a requirement. Maintaining confidentiality and privacy will also be issues if you are transferring personal data.
Performance:
For a grid performance is the main key is to deliver nontrivial qualities of service “. Some grid services might fall short because
the scattering and gathering steps can incur significant delay. Grid computing tends to be opportunistic – it must wait for computing resources to become idle – which means that performance can be nondeterministic. Grid performances include resource availability and reliability, utilization and load, response time, delay and delay variation. Data Integrity is another consideration .
5: Applications:
1: Bio-Informatics:
Bioinformatics analysis of data produced by complete genome sequencing projects is one of the major challenges. Integrating up-to-date databanks and relevant algorithms is a clear requirement of such an analysis. Grid computing would be a viable solution to distribute algorithms and data, computing and storage resources for Genomics.
When bioinformatics grid server receives the computational requests from the client, it locates a suitable node in the grid to perform the mathematical computation according to the users’ requirement and task allocation rule, or integrates a virtual supercomputer to perform the larger computational requests from users.
2. INTRODUCTION TO COMPUTING
3. TYPES OF GRID COMPUTING
4. ISSUES
5. APPLICATIONS
6. A SIMPLE HELLO WORLD EXAMPLE
7. DOWNSIDESOF GRID COMPUTING
8. CONCLUSION
1: ABSTRACT:
Grid computing is said to be the next big thing in IT. Research in grid computing is making rapid progress, owing to the increasing need for large-scale computation in the resolution of complex problems.
Clusters are, in a sense, the predecessors of grid technology. Clusters interconnect nodes through a local high-speed network, using commodity hardware, with the aim of reducing the costs of such infrastructures.
Supercomputers have been replaced by clusters of workstations in a large number of research projects.
Grids provide access to widely distributed computing and data resources, allowing data-intensive applications significantly improved data access, management and analysis. Nowadays there are a huge number of data intensive applications in several domains such as physics, climate modeling, biology/bio-informatics, addressing some of the most important current problems.
Computing grids are conceptually not unlike electrical grids. When you connect to the electrical grid, you don’t need to know where the power plant is or how the current gets to you. Grid computing uses middleware to coordinate disparate IT resources across a network, allowing them to function as a virtual whole.
Grids use a layer of middleware to communicate with and manipulate heterogeneous hardware and data sets. In some fields— astronomy, for example—hardware cannot reasonably be moved and is prohibitively expensive to replicate on other sites.
Grids address two distinct but related goals: providing remote access to IT assets, and aggregating processing power. The most obvious resource included in a grid is a processor, but grids also encompass sensors, data-storage systems, applications, and other resources.
Grids use a layer of middleware to communicate with and manipulate heterogeneous hardware and data sets. In some fields— astronomy, for example—hardware cannot reasonably be moved and is prohibitively expensive to replicate on other sites.
Many grids are appearing in the sciences, in fields such as chemistry, physics, and genetics, and cryptologists and mathematicians have also begun working with grid computing. Grid technology has the potential to significant impact other areas of study with heavy computational requirements, such as urban planning. Another important area for the technology is animation, which requires massive amounts of computational power and is a common tool in a growing number of disciplines included in a grid is a processor, but grids also encompass sensors, data-storage systems, applications, and other resources.
2: INTRODUCTION
TO COMPUTING:
Grid computing is an implementation in an enterprise computing taxonomy .It consists of family of technologies for opportunistically providing computing power from a pool of resources. Grid computing is opportunistic since it has to wait for resources to become available. The resources may include computing cycles, file and data storage, caching, network bandwidth, databases and application software. These resources can be distributed diversely on the globe .Provision of computer power means the methods and mechanisms for locating, authorizing, assembling, scheduling, releasing and accounting for resources and their usage.
For example compute grids share computational and data resources. And some grids share both and can also share network bandwidth, storage and caching resources and application software.
So the first dimension reflects the types of resources that the grid can use .Second dimension describes a grids geographic or administrative reach .Third dimension tells how the companies can get the resources. Fourth dimension reflects the partnerships between the Enterprises. The Fifth dimension reflects for what type of application a grid is used for biology, sensors or any other access.
So this proves that a Grid is multidimensional.
Coming to the Cluster, they are connected commonly connected to a high speed LANS. Clusters are usually deployed to improve speed and/or reliability over that provided by a single computer, while typically being much more cost-effective than single computers of comparable speed or reliability. They can be geographically distributed, but are often closely coupled in the same room.
Clusters can consist of heterogeneous processors and peripherals but they are homogeneous and use high performance and special purpose interconnection networks.
Fig: clusters in a university
But a CLUSTER is not a grid.
Since Computer Clusters require a much higher degree of centralized control, this point clearly distinguishes between a cluster and a grid.
Mainly the grid community focuses on issues such as Reliability, Security, Service and Quality Performance and Resource integration.
3:TYPES OF GRID COMPUTING:
1: Utility Computing:
Here, the main idea is to offer computing resources as an on-demand service to customers in much the same way that utilities offer electrical, gas, water, and telephone services to households and businesses. The utility computing service provider offers hosted computing resources.
One distinction is that the on-demand computing resources can comprise a grid in the service provider’s realm, and the grid can span several sites in the provider’s service area. Grid economies and scalability add a new dimension.
2: Autonomic computing:
Autonomic computing architectures monitor utilization and performance, tune and manage themselves, and adapt to failure. Some share resources and schedule tasks with other systems. The fundamental components of an autonomic computing system provide functions that computing grids will almost certainly need to operate effectively, such as the ability to recover lost computational subtasks.
As grids evolve, they might take on many of the characteristics of an autonomic computing system: Self-monitoring, diagnosis, and adaptability in their youth; sophisticated resource scheduling and forecasting; and perhaps a vertebrate-like involuntary autonomic nervous system at maturity. So the real issue is the extent to which a grid has adopted the characteristics of autonomic computing.
3: Peer-to-peer computing:
Peer-to-peer computing is one type of application that uses grid services to advertise, find, and share files.
The grid community tends to focus on top-down issues such as
1: resource integration,
2: performance,
3: reliability,
4: service quality, and
5: security.
The peer-to-peer community tends to focus on bottom up issues such as narrowly defined and specialized services, and support for tens of thousands of concurrent participants.
4: ISSUES:
The success of grid computing depends on fundamental issues in 2 main areas:
1: security
2: performance
Security:
Grids must deal with every security that any enterprise-owned or outsourced computing model faces. Security issues include secure authentication, access rights and privileges. Reliable and secure communications, perhaps with encryption, are also a requirement. Maintaining confidentiality and privacy will also be issues if you are transferring personal data.
Performance:
For a grid performance is the main key is to deliver nontrivial qualities of service “. Some grid services might fall short because
the scattering and gathering steps can incur significant delay. Grid computing tends to be opportunistic – it must wait for computing resources to become idle – which means that performance can be nondeterministic. Grid performances include resource availability and reliability, utilization and load, response time, delay and delay variation. Data Integrity is another consideration .
5: Applications:
1: Bio-Informatics:
Bioinformatics analysis of data produced by complete genome sequencing projects is one of the major challenges. Integrating up-to-date databanks and relevant algorithms is a clear requirement of such an analysis. Grid computing would be a viable solution to distribute algorithms and data, computing and storage resources for Genomics.
When bioinformatics grid server receives the computational requests from the client, it locates a suitable node in the grid to perform the mathematical computation according to the users’ requirement and task allocation rule, or integrates a virtual supercomputer to perform the larger computational requests from users.
2: SMALLPOX project:We intend to use grid computing to screen millions of potential anti-smallpox drugs against this target.
The Smallpox Research Grid uses a SETI-like model to analyze interactions between virus protein targets and a catalog of tens of millions of drug molecules. The Smallpox project can harness millions of computers belonging to people in over two hundred countries, all of whom will benefit from protection against smallpox.
By adding your CPU to the global grid, every time your computer is idle, you contribute your computing resources to the grid, accelerating the screening process while dramatically reducing the cost of the project.
The result is that rather than spending years to screen hundreds of thousands of molecules, it will be possible to screen hundreds of millions of molecules in just months.
This saves a large amount of system time and alters the use of Resources.
3: Grid Computing In SETI:
SETI, the search for Extraterrestrial Intelligence uses a huge number of Internet-connected computers to download the results during idle times.
As of late 2004, SETI had scavenged 1.83 million years of CPU time from 4.9 million users in 226 countries .It had used this grid to perform 4.5*10( power)21 floating-point operations Experts say that 10(power)21 -one sextillion-is the approximate number of grains of sand on all of Earth's beaches and deserts
It is just one order of magnitude shy of the estimated number of stars in the visible universe.
Some SETI observations have been conducted using the radio telescope
4: The Rice Genome Program: :
Bioinformatics research leads to a lot of information collected worldwide for which large databases should be maintained .Grid computing solves this problem. Grid computing would be a viable solution to distribute algorithms and data, computing and storage resources for Genomics.
Finding a single genome of Rice (scientific name Oryza sativa) can take a lot of time which measures up to months examining all the base pairs which are in millions These data is stored in data repositories. Hence we require a technology not only to visualize analyze DNA data but also the integration and exchange of information on a gene or coding regions from different international collaborative databases needs to be done in a careful and in a robust manner .Grid Technology Solves this problem.
Grid Technology enables sharing of bioinformatics data from different files by creating a virtual organization of data.
So the collection of databases generated during the research work on RICE is collected and maintained by a grid which helps in posing Queries on a particular type of Rice.
Here the user must provide the services they want providing constraints like family size , protein interactions ..etc .
6: A simple Hello world Example:
Let us consider some cases of web client-server applications like Video streaming Game serving, File downloading etc. So an approach to provide a scalable solution is to distribute the application even to the other servers that run the same application. A Network dispatcher is the entry point for an application but does not run the application , rather the servers which are connected onto the same LAN handle the workload and answers the queries of the client.
Let us consider an example: A network dispatcher (or) Front end server waits for client requests. When connected the client is given back a ticket and an application service IP address of where to connect.
The application answers HELLO WORLD when the client connects to it . The application is started on the application servers by the front end server.
The Executable for the client is Hello client and takes the front end server host name as parameter.
Grid computing used in Hello world Example .
7:Downsides of Grid Computing:
Being able to access distant IT assets—and have them function seamlessly with tools on different platforms—can be a boon to researchers, but it presents real security concerns to organizations responsible for those resources. An institution that makes its IT assets available to researchers or students on other campuses and in other countries must be confident that its involvement does not expose those assets to unnecessary risks. Similarly, directors of research projects will be reluctant to take advantage of the opportunities of a grid without assurances that the integrity of the project, its data, and its participants will be protected.
Another challenge facing grids is the complexity in building middleware structures that can knit together collections of resources to work as a unit across network connections that often span oceans and continents. Scheduling the availability of IT resources connected to a grid can also present new challenges to organizations that manage those resources. Increasing standardization of protocols addresses some of the difficulty in creating smoothly functioning grids, but, by their nature, grids that can provide unprecedented access to facilities and tools involve a high level of complexity.
A word of caution should be given to the overly enthusiastic. The grid is not a silver bullet that can take any application and run it a 1000 times faster without the need for buying any more machines or software. Not every application is suitable or enabled for running on a grid.
Some kinds of applications simply cannot be parallelized. For others, it can take a large amount of work to modify them to achieve faster throughput. The configuration of a grid can greatly affect the performance, reliability, and security of an organization’s computing infrastructure. For all of these reasons, it is important for us to understand how far the grid has evolved today and which features are coming tomorrow or in the distant future.
8: CONCLUSION:
A greater awareness of this area is needed so that people can make a direct contribution towards solving these problems by providing whatever spare computing resources they may have at their disposal (usually in the form of idle cycles). Grid computing is the future for Bio-Informatics which helps to create an epidemic free future for man kind and to solve long-term problems. Grids make research projects possible that formerly were impractical or unfeasible due to the physical location of vital resources.
Using a grid, researchers in Great Britain, for example, can conduct research that relies on databases across Europe, instrumentation in Japan, and computational power in the United States. Making resources available in this way exposes students to the tools of the profession, facilitating new possibilities for research and instruction, particularly at the undergraduate level.
Although speeds and capacities of processors continue to increase, resource-intensive applications are proliferating as well. At many institutions, certain campus users face ongoing shortages of computational power, even as large numbers of computers are underused. With grids, programs previously hindered by constraints on computing power become possible.
- PAPER ON GRID COMPUTING
Abstract
Grid Computing delivers on the potential in the growth and abundance of network connected systems and bandwidth: computation, collaboration and communication over the Advanced Web. This paper deals with various grid concepts.In particular it is shown what advantages a utilization of grid computing may have to offer and which applications could benefit from it.Moreover the notion of grid learning object is introduced.
Introduction
Increased network bandwidth, more powerful computers, and the acceptance of the Internet have driven the on-going demand for new and better ways to compute. Commercial enterprises, academic institutions, and research organizations continue to take advantage of these advancements, and constantly seek new technologies and practices that enable them to seek new ways to conduct business. However, many challenges remain. Increasing pressure on development and research costs, faster time-to-market, greater throughput, and improved quality and innovation are always foremost in the minds of administrators - while computational needs are outpacing the ability of organizations to deploy sufficient resources to meet growing workload demands.
On top of these challenges is the need to handle dynamically changing workloads. The truth is, flexibility is key. In a world with rapidly changing markets, both research institutions and enterprises need to quickly provide compute power where it is needed most. Indeed, if systems could be dynamically created when they are needed, teams could harness these resources to increase innovation and better achieve their objectives.
1.Grid Overview
Grid Computing delivers on the potential in the growth and abundance of network connected systems and bandwidth: computation, collaboration and communication over the Advanced Web. At the heart of Grid Computing is a computing infrastructure that provides dependable, consistent, pervasive and inexpensive access to computational capabilities. By pooling federated assets into a virtual system, a grid provides a single point of access to powerful distributed resources.
Researchers working to solve many of the most difficult scientific problems have long understood the potential of such shared distributed computing systems. Development teams focused on technical products, like semiconductors, are using Grid Computing to achieve higher throughput. Likewise, the business community is beginning to recognize the importance of distributed systems in applications such as data mining and economic modeling.
With a grid, networked resources -- desktops, servers, storage, databases, and even scientific instruments -- can be combined to deploy massive computing power wherever and whenever it is needed most. Users can find resources quickly,use them efficiently and scale them seamlessly.
2.The Grid Concept
The term ‘grid’ is variously used to describe a number of different, but related, ideas, including utility computing concepts, grid technologies, and grid standards. In this paper the term ‘Grid’ is used in the widest sense to describe the ability to pool and share Information Technology (IT) resources in a global environment in a manner which achieves seamless, secure, transparent, simple access to a vast collection of many different types of hardware and software resources, (including compute nodes, software codes, data repositories, storage devices, graphics and terminal devices and instrumentation and equipment), through non-dedicated
wide area networks, to deliver customized resources to specific applications.
At the most general level Grid is independent of any specific standard or technology. Any practical grid is realized through specific distributed computing
technologies and standards that can support the necessary interoperability. Today, there are no universally agreed grid standards, but there are freely available, open source and proprietary grid technologies that implement emerging standards recommendations. Separate web services standards are also emerging which have many grid-like capabilities. Indeed grids are already being built by integrating and enhancing web standards technology.
3.Practical Realizations
Practical grids are generally described in terms of layers (see Fig 1). The lowest layers (the ‘platform’) comprise the hardware resources, including computers, networks, databases, instruments, and interface devices. These devices, which will be geographically distributed, may present their data in very different formats, are likely to have different qualities of service (e.g. communication speeds, bandwidth) and are likely to utilize different operating systems and processor architectures. A key concept is that the hardware resources can change over
time - some may be withdrawn, upgraded or replaced by newer models, others may change their performance to adapt to local conditions - for example restrictions in the available communications bandwidth.
The middle layers (sometimes referred to as ‘middleware’) provide a set of software functions that ‘buffer’ the user from administrative tasks associated
with access to the disparate resources. These functions are made available as services and some provide a ‘jacket’ around the hardware interfaces, such that the different hardware platforms present a unified interface to different applications. Other functions manage the underlying fabric, such as identification and scheduling of resources in a secure and auditable way. The middle layer also provides the ability to make frequently used patterns of functions available as a composed higher-level service using workflow techniques.
The highest layers contain the user ‘application services’. Pilot projects have already been carried out in user application areas, such as life sciences
(e.g. computational biology, genomics), engineering (e.g. simulation and modeling, just in time maintenance) and healthcare (e.g. diagnosis, telematics). These services could include horizontal functions such as workflow (the
linkage of multiple services into a single service), web portals, data visualization and the language/semantic concepts appropriate to different application sectors.
4.Grid Developments and Deployment
A key issue facing the industry is the timing and mode of deployment of Grid technology to ensure that it is sufficiently mature to deliver the expected business
benefits. There is emerging evidence that the technology can achieve significant operational benefits (e.g. in telemedicine), improvements in performance (e.g. in climate modeling and genomics) and a significant reduction in costs. Nevertheless, current grid technologies are not yet viewed as sufficiently mature for industry scale use, and remain largely unproven in terms of security, reliability, scalability, and performance.
4.1.Short term
For the short term (within the next two years), Grid is most likely to be introduced into large organizations as internal ‘Enterprise grids’, i.e. built behind firewalls and used within a limited trust domain, perhaps with controlled links to external grids. A good analogy would be the adoption into business of the Internet, where the first step was often the roll out of a secure internal company ‘Intranet’, with a gradual extension of capabilities (and hence opportunity for misuse) towards fully ubiquitous Internet access. Centralized management is expected to be the only way to guarantee qualities of service. Typically users of this early technology will be expecting to achieve IT cost reduction, increased efficiency, some innovation and flexibility in business processes. At the same time the distinction between web services and grid services is expected to disappear, with
the capabilities of one merging into the other and the interoperability between the two standards being taken for granted.
4.2.Medium Term
In the mid term (say a five year timeframe) expect to see wider adoption - largely for resource virtualization and mass access. The technology will be particularly appropriate for applications that utilize broadband and mobile/air interfaces, such as on-line gaming, ‘visualization-on-demand’ and applied industrial research. The emphasis will move from use within a single organization to use across organizational domains and within Virtual Organizations, requiring issues such as ownership, management and accounting to be handled within trusted partnerships. There will be a shift in value from provision of computer power to provision of information and knowledge. At the same time open standards based tooling for building service oriented applications are likely to emerge and Grid technology will start to be incorporated into off-the-shelf’ products. This will lead to standard consumer access to virtualized compute and data resources, enabling a whole new range of consumer services to be delivered.
4.3.Long term
In the longer term, Grid is likely to become a prerequisite for business success - central to business processes, new types of service, and a central component of product development and customer solutions. A key business change will be the establishment of trusted service providers, probably acting on a global scale and
disrupting the current supply chains and regulatory environments.
5.Conclusions
5.1.The Grid -- the IT infrastructure of the future -- promises to transform computation, communication, and collaboration. Over time, these will be seen in the context of grids -- academic grids, enterprise grids, research grids, entertainment grids, community grids, and so on. Grids will become service-driven with lightweight clients accessing computing resources over the Internet. Datacenters will be safe, reliable, and available from anywhere in the world. Applications will be part of a wide spectrum of network-delivered services that include compute cycles, data processing tools, accounting and monitoring, and more.
5.2.Grid computing and related technologies will only be adopted by commercial users if they are confident that their data and privacy can be adequately protected and that the Grid will be at least as scaleable, robust and reliable as their own in-house IT systems. Thus, new Internet technologies and standards such as IPv6 take on even greater importance. Needless to say, users of the Grid want easy, affordable, ubiquitous, broadband access to the Internet.
5.3.Similar to the public policy issues raised by the development of electronic commerce and electronic government, Grids raise a number of public policy issues: data privacy, information and cyber security, liability, antitrust, intellectual property, access, taxes, tariffs, as well as usage for education, government, and regional development.
Grid Computing delivers on the potential in the growth and abundance of network connected systems and bandwidth: computation, collaboration and communication over the Advanced Web. This paper deals with various grid concepts.In particular it is shown what advantages a utilization of grid computing may have to offer and which applications could benefit from it.Moreover the notion of grid learning object is introduced.
Introduction
Increased network bandwidth, more powerful computers, and the acceptance of the Internet have driven the on-going demand for new and better ways to compute. Commercial enterprises, academic institutions, and research organizations continue to take advantage of these advancements, and constantly seek new technologies and practices that enable them to seek new ways to conduct business. However, many challenges remain. Increasing pressure on development and research costs, faster time-to-market, greater throughput, and improved quality and innovation are always foremost in the minds of administrators - while computational needs are outpacing the ability of organizations to deploy sufficient resources to meet growing workload demands.
On top of these challenges is the need to handle dynamically changing workloads. The truth is, flexibility is key. In a world with rapidly changing markets, both research institutions and enterprises need to quickly provide compute power where it is needed most. Indeed, if systems could be dynamically created when they are needed, teams could harness these resources to increase innovation and better achieve their objectives.
1.Grid Overview
Grid Computing delivers on the potential in the growth and abundance of network connected systems and bandwidth: computation, collaboration and communication over the Advanced Web. At the heart of Grid Computing is a computing infrastructure that provides dependable, consistent, pervasive and inexpensive access to computational capabilities. By pooling federated assets into a virtual system, a grid provides a single point of access to powerful distributed resources.
Researchers working to solve many of the most difficult scientific problems have long understood the potential of such shared distributed computing systems. Development teams focused on technical products, like semiconductors, are using Grid Computing to achieve higher throughput. Likewise, the business community is beginning to recognize the importance of distributed systems in applications such as data mining and economic modeling.
With a grid, networked resources -- desktops, servers, storage, databases, and even scientific instruments -- can be combined to deploy massive computing power wherever and whenever it is needed most. Users can find resources quickly,use them efficiently and scale them seamlessly.
2.The Grid Concept
The term ‘grid’ is variously used to describe a number of different, but related, ideas, including utility computing concepts, grid technologies, and grid standards. In this paper the term ‘Grid’ is used in the widest sense to describe the ability to pool and share Information Technology (IT) resources in a global environment in a manner which achieves seamless, secure, transparent, simple access to a vast collection of many different types of hardware and software resources, (including compute nodes, software codes, data repositories, storage devices, graphics and terminal devices and instrumentation and equipment), through non-dedicated
wide area networks, to deliver customized resources to specific applications.
At the most general level Grid is independent of any specific standard or technology. Any practical grid is realized through specific distributed computing
technologies and standards that can support the necessary interoperability. Today, there are no universally agreed grid standards, but there are freely available, open source and proprietary grid technologies that implement emerging standards recommendations. Separate web services standards are also emerging which have many grid-like capabilities. Indeed grids are already being built by integrating and enhancing web standards technology.
3.Practical Realizations
Practical grids are generally described in terms of layers (see Fig 1). The lowest layers (the ‘platform’) comprise the hardware resources, including computers, networks, databases, instruments, and interface devices. These devices, which will be geographically distributed, may present their data in very different formats, are likely to have different qualities of service (e.g. communication speeds, bandwidth) and are likely to utilize different operating systems and processor architectures. A key concept is that the hardware resources can change over
time - some may be withdrawn, upgraded or replaced by newer models, others may change their performance to adapt to local conditions - for example restrictions in the available communications bandwidth.
The middle layers (sometimes referred to as ‘middleware’) provide a set of software functions that ‘buffer’ the user from administrative tasks associated
with access to the disparate resources. These functions are made available as services and some provide a ‘jacket’ around the hardware interfaces, such that the different hardware platforms present a unified interface to different applications. Other functions manage the underlying fabric, such as identification and scheduling of resources in a secure and auditable way. The middle layer also provides the ability to make frequently used patterns of functions available as a composed higher-level service using workflow techniques.
The highest layers contain the user ‘application services’. Pilot projects have already been carried out in user application areas, such as life sciences
(e.g. computational biology, genomics), engineering (e.g. simulation and modeling, just in time maintenance) and healthcare (e.g. diagnosis, telematics). These services could include horizontal functions such as workflow (the
linkage of multiple services into a single service), web portals, data visualization and the language/semantic concepts appropriate to different application sectors.
4.Grid Developments and Deployment
A key issue facing the industry is the timing and mode of deployment of Grid technology to ensure that it is sufficiently mature to deliver the expected business
benefits. There is emerging evidence that the technology can achieve significant operational benefits (e.g. in telemedicine), improvements in performance (e.g. in climate modeling and genomics) and a significant reduction in costs. Nevertheless, current grid technologies are not yet viewed as sufficiently mature for industry scale use, and remain largely unproven in terms of security, reliability, scalability, and performance.
4.1.Short term
For the short term (within the next two years), Grid is most likely to be introduced into large organizations as internal ‘Enterprise grids’, i.e. built behind firewalls and used within a limited trust domain, perhaps with controlled links to external grids. A good analogy would be the adoption into business of the Internet, where the first step was often the roll out of a secure internal company ‘Intranet’, with a gradual extension of capabilities (and hence opportunity for misuse) towards fully ubiquitous Internet access. Centralized management is expected to be the only way to guarantee qualities of service. Typically users of this early technology will be expecting to achieve IT cost reduction, increased efficiency, some innovation and flexibility in business processes. At the same time the distinction between web services and grid services is expected to disappear, with
the capabilities of one merging into the other and the interoperability between the two standards being taken for granted.
4.2.Medium Term
In the mid term (say a five year timeframe) expect to see wider adoption - largely for resource virtualization and mass access. The technology will be particularly appropriate for applications that utilize broadband and mobile/air interfaces, such as on-line gaming, ‘visualization-on-demand’ and applied industrial research. The emphasis will move from use within a single organization to use across organizational domains and within Virtual Organizations, requiring issues such as ownership, management and accounting to be handled within trusted partnerships. There will be a shift in value from provision of computer power to provision of information and knowledge. At the same time open standards based tooling for building service oriented applications are likely to emerge and Grid technology will start to be incorporated into off-the-shelf’ products. This will lead to standard consumer access to virtualized compute and data resources, enabling a whole new range of consumer services to be delivered.
4.3.Long term
In the longer term, Grid is likely to become a prerequisite for business success - central to business processes, new types of service, and a central component of product development and customer solutions. A key business change will be the establishment of trusted service providers, probably acting on a global scale and
disrupting the current supply chains and regulatory environments.
5.Conclusions
5.1.The Grid -- the IT infrastructure of the future -- promises to transform computation, communication, and collaboration. Over time, these will be seen in the context of grids -- academic grids, enterprise grids, research grids, entertainment grids, community grids, and so on. Grids will become service-driven with lightweight clients accessing computing resources over the Internet. Datacenters will be safe, reliable, and available from anywhere in the world. Applications will be part of a wide spectrum of network-delivered services that include compute cycles, data processing tools, accounting and monitoring, and more.
5.2.Grid computing and related technologies will only be adopted by commercial users if they are confident that their data and privacy can be adequately protected and that the Grid will be at least as scaleable, robust and reliable as their own in-house IT systems. Thus, new Internet technologies and standards such as IPv6 take on even greater importance. Needless to say, users of the Grid want easy, affordable, ubiquitous, broadband access to the Internet.
5.3.Similar to the public policy issues raised by the development of electronic commerce and electronic government, Grids raise a number of public policy issues: data privacy, information and cyber security, liability, antitrust, intellectual property, access, taxes, tariffs, as well as usage for education, government, and regional development.
- SURFACE PLASEMON RESONANCE
INTRODUCTION
During the last two decades we have witnessed remarkable research and development activity aimed at the realization of optical sensors for the measurement of chemical and biological quantities. First optical chemical sensors were based on the measurement of changes in absorption spectrum and were developed for the measurement of CO2 and O2 concentration. Since then a large variety of optical methods have been used in chemical sensors and biosensors including elipsometry, spectroscopy, interferometry spectroscopy of guided modes in optical wave guide structures and surface plasmon resonance .
The potential of surface plasmon resonance for characterization of thin films and monitoring process at metal interfaces was recognized in the late seventies. In 1982 the use of SPR for gas detection and biosensing was demonstrated by Nylander and lieberg . Since then SPR sensing has been receiving continuously growing attention from scientific community. Development of new SPR sensing configurations as well as applications of SPR sensing devices for the measurement of physical , chemical and biological quantities have been described .
The SPR sensor technology has been commercialized by several companies and become a leading technology in the field of direct real time observation of the biomolecular interaction . The phenomenon of anomalous diffraction on diffraction gratings due to the excitation of surface plasma waves was first described in the beginning of the twentieth century by Wood. In the late sixties, optical excitation of surface plasmons by the method of attenuated total reflection was demonstrated by Kretschmann and Otto .
ABSTRACT
Surface plasmon resonance (SPR) is a phenomenon occurring at metal surfaces(typically gold and silver) when an incident light beam strikes the surface at a particular angle.Depending on the thickness of a molecular layer at the metal surface,the SPR phenomenon results in a graded reduction in intensity of the reflected light.Biomedical applications take advantage of the exquisite sensitivity of SPR to the refractive index of the medium next to the metal surface, which makes it possible to measure accurately the adsorption of molecules on the metal surface an their eventual interactions with specific ligands. The last ten years have seen a tremendous development of SPR use in biomedical applications.
The technique is applied not only to the measurement in real time of the kinetics of ligands receptor interactions and to the screening of lead compounds in the pharmaceutical industry, but also to the measurement DNA hybridization, enzyme- substrate interactions, in polyclonal antibody characterization, epitope mapping, protein conformation studies and label free immunoassays.
Conventional SPR is applied in specialized biosensing instruments. These instruments use expensive sensor chips of limited reuse capacity and require complex chemistry for ligand or protein immobilization. Laboratory has successfully applied SPR with colloidal gold particles in buffered solutions. This application offers many advantages over conventional SPR. The support is cheap, easily synthesized, and can be coated with various proteins or protein ligand complexes by charge adsorption. With colloidal gold, the SPR phenomenon can be monitored in any UV spectrophotometer. For high throughput applications we have adapted the technology in an automated clinical chemistry analyzer.
This simple technology finds application in label free quantitative immunoassay techniques for proteins and small analytes, in conformational studies with proteins as well as real time association dissociation measurements of receptor ligand interactions for high throughput screening and lead optimization.
AIR MUSCLES
AIR MUSCLES
ABSTRACT
Air muscle is essentially a robotic actuator which is replacing the conventional pneumatic cylinders at a rapid pace. Due to their low production costs and very high power to weight ratio, as high as 400:1, the preference for Air Muscles is increasing. Air Muscles find huge applications in bio robotics and development of fully functional prosthetic limbs, having superior controlling as well as functional capabilities compared with the current models. This paper discusses Air Muscles in general, their construction, and principle of operation, operational characteristics and applications.
INTRODUCTION
Robotic actuators conventionally are pneumatic or hydraulic devices. They have many inherent disadvantages like low operational flexibility, high safety requirements, and high cost operational as well as constructional etc. The search for an actuator which would satisfy all these requirements ended in Air Muscles. They are easy to manufacture, low cost and can be integrated with human operations without any large scale safety requirements. Further more they offer extremely high power to weight ratio of about 400:1. As a comparison electric motors only offer a power ration of 16:1. Air Muscles are also called McKibben actuators named after the researcher who developed it.
History
It was in 1958 that R.H.Gaylord invented a pneumatic actuator which’s original applications included a door opening arrangement and an industrial hoist. Later in 1959 Joseph.L.McKibben developed Air Muscles. The source of inspiration was the human muscle itself, which would swell when a force has to be applied. They were developed for use as an orthotic appliance for polio patients. Clinical trials were realized in 1960s. These muscles were actually made from pure rubber latex, covered by a double helical weave (braid) which would contract when expanded radially. This could actually be considered as a biorobotic actuator as it operates almost similar to a biological muscle.
Air Muscle Schematic- McKibben Model
The current form air muscles were developed by the Bridgestone Company, famous for its tires. The primary material was rubber i.e. the inner tube was made from rubber. Hence these actuators were called ‘Rubbertuators’. These developments took place around 1980s.Later in 1990s Shadow Robotic Company of the United Kingdom began developing Air Muscles. These are the most commonly used air muscles now and are associated with almost all humanoid robotic applications which were developed recently. Apart from Shadow another company called The Merlin Humaniform develops air muscles for the same applications, although their design is somewhat different from the Shadow muscles.
- GDI-Gasoline Direct Injection
ABSTRACT
Gasoline direct injection (GDI) engine technology has received considerable attention over the last few years as a way to significantly improve fuel efficiency without making a major shift away from conventional internal combustion technology. In many respects, GDI technology represents a further step in the natural evolution of gasoline engine fueling systems. Each step of this evolution, from mechanically based carburetion, to throttle body fuel injection, through multi-point and finally sequential multi-point fuel injection, has taken advantage of improvements in fuel injector and electronic control technology to achieve incremental gains in the control of internal combustion engines.
Further advancements in these technologies, as well as continuing evolutionary advancements in combustion chamber and intake valve design and combustion chamber flow dynamics, have permitted the production of GDI engines for automotive applications. Mitsubishi, Toyota and Nissan all market four- stroke GDI engines in Japan.
Further advancements in these technologies, as well as continuing evolutionary advancements in combustion chamber and intake valve design and combustion chamber flow dynamics, have permitted the production of GDI engines for automotive applications. Mitsubishi, Toyota and Nissan all market four- stroke GDI engines in Japan.
Major Objectives of the GDI engine
• Ultra-low fuel consumption that betters that of even diesel engines
• Superior power to conventional MPI engines
• Superior power to conventional MPI engines
Sophisticated high-pressure injectors capable of producing very fine, well-defined fuel sprays, coupled with advanced charge air control techniques, now make stable GDI combustion feasible. There are impediments to widespread GDI introduction, however, especially in compliance with stringent emission standards. This report addresses both the efficiencies inherent in GDI technology and the emissions constraints that must be addressed before GDI can displace current spark-ignition engine technology.
In this seminar I am intending to familiarize the working of this technology, which has the capability to become the turning point in the development of diesel engine technology
WHY NOT CARBURETTOR?
All Internal combustion engines burn fuel in air and every fuel has ideal air ratio at which it will ignite or burn as completely as possible. The challenge that faces engineers is to introduce the perfect or precise proportions of fuel and air required for complete combustion. This is commonly referred to as the stoichiometric ratio. Petrol has a stoichiometric ratio of 14.7:1(14.7 parts of air with 1 part of fuel by weight). This ratio has to be maintained under the varying engine loads and conditions. The carb earlier did this metering with its ancillaries. But the carb has its limits and though performance and economy with modern carbs were acceptable, a seamless power delivery and emissions often suffered.
Carburetor has following disadvantages
• Vapour lock
• Perfect air/fuel mixture cannot be obtained
• Lack of throttle response
• Low volumetric efficiency
• Icing – problem in aircraft engines
• Mechanical device
• Compromises on emission
• Perfect air/fuel mixture cannot be obtained
• Lack of throttle response
• Low volumetric efficiency
• Icing – problem in aircraft engines
• Mechanical device
• Compromises on emission
- F1 CARS
INTRODUCTION
Car racing is one of the most technologically advanced sports in the world today. Race Cars are the most sophisticated vehicles that we see in common use. It features exotic, high-speed, open-wheel cars racing all around the world. The racing teams have to create cars that are flexible enough to run under all conditions. This level of diversity makes a season of F1 car racing incredibly exciting. The teams have to completely revise the aerodynamic package, the suspension settings, and lots of other parameters on their cars for each race, and the drivers have to be extremely agile to handle all of the different conditions they face. Their carbon fiber bodies, incredible engines, advanced aerodynamics and intelligent electronics make each car a high-speed research lab.
A F1 Car runs at speeds up to 240 mph, the driver experiences G-forces and copes with incoming data so quickly that it makes Car driving one of the most demanding professions in the sporting world. F1 car is an amazing machine that pushes the physical limitations of automotive engineering. On the track, the driver shows off his professional skills by directing around an oval track at speeds
Formula One Grand Prix racing is a glamorous sport where a fraction of a second can mean the difference between bursting open the bubbly and struggling to get sponsors for the next season’s competition. To gain those extra milliseconds, all the top racing teams have turned to increasingly sophisticated network technology.
Much more money is spent in F1 these days. This results highest tech cars. The teams are huge and they often fabricate their entire racers. F1′s audience has grown tremendously throughout the rest of the world. .
Much more money is spent in F1 these days. This results highest tech cars. The teams are huge and they often fabricate their entire racers. F1′s audience has grown tremendously throughout the rest of the world. .
In an average street car equipped with air bags and seatbelts, occupants are protected during 35-mph crashes into a concrete barrier. But at 180 mph, both the car and the driver have more than 25 times more energy. All of this energy has to be absorbed in order to bring the car to a stop. This is an incredible challenge, but the cars usually handle it surprisingly well
F1 Car driving is a demanding sport that requires precision, incredibly fast reflexes and endurance from the driver. A driver’s heart rate typically averages 160 beats per minute throughout the entire race. During a 5-G turn, a driver’s arm — which normally weighs perhaps 20 pounds — weighs the equivalent of 100 pounds. One thing that the G forces require is constant training in the weight room. Drivers work especially on muscles in the neck, shoulders, arms and torso so that they have the strength to work against the Gs.
Drivers also work a great deal on stamina, because they have to be able to perform throughout a three-hour race without rest. One thing that is known about F1 Car drivers is that they have extremely quick reflexes and reaction times compared to the norm. They also have extremely good levels of concentration and long attention spans. Training, both on and off the track, can further develop these skills.
THE CHASIS
Modern f1 Cars are defined by their chassis. All f1 Cars share the following characteristics:
They are single-seat cars.
They have an open cockpit.
They have open wheels — there are no fenders covering the wheels.
They have wings at the front and rear of the car to provide downforce.
They position the engine behind the driver..
They are single-seat cars.
They have an open cockpit.
They have open wheels — there are no fenders covering the wheels.
They have wings at the front and rear of the car to provide downforce.
They position the engine behind the driver..
The tub must be able to withstand the huge forces produced by the high cornering speeds, bumps and aerodynamic loads imposed on the car. This chassis model is covered in carbon fibre to create a mould from which the actual chassis can be made. Once produced the mould is smoothed down and covered in release agent so the carbon-fibre tub can be easily removed after manufacture.
The mould is then carefully filled inside with layers of carbon fibre. This material is supplied like a typical cloth but can be heated and hardened. The way the fibre is layered is important as the fibre can direct stresses and forces to other parts of the chassis, so the orientation of the fibres is crucial. The fibre is worked to fit exactly into the chassis mould, and a hair drier is often used to heat up the material, making it stick, and to help bend it to the contours of the mould.
After each layer is fitted, the mould is put into a vacuum machine to literally suck the layers to the mould to make sure the fibre exactly fits the mould. The number of layers in the tub differs from area to area, but more stressed parts of the car have more, but the average number is about 12 layers. About half way between these layers there is a layer of aluminum honeycomb that further adds to the strength.
Once the correct numbers of layers have been applied to the mould, it is put into a machine called an autoclave where it is heated and pressurized. The high temperatures release the resin within the fibre and the high pressure (up to 100 psi) squeezes the layer together. Throughout this process, the fibres harden and become solid and the chassis is normally ready in two and a half hours. The internals such as pedals, dashboard and seat back are glued in place with epoxy resin and the chassis painted to the sponsor’s requirements.
