Abstract: Grid computing is more than just communicating between computers: it is a way to share computing power. It is basically a form of networking .Unlike conventional networks that focus on communication among devices, grid computing harnesses unused processing cycles of all computers in a network involving huge amounts of data and for solving problems too intensive for any stand-alone machine. It allows us to unite pools of servers, storage systems and networks into a single large system so we 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. As a result of the invention of technically faster hardware and more sophisticated software, in the recent years we have seen a substantial increase in the network performance.
Nevertheless, there are still problems, in the fields of science, engineering, and business, which cannot be effectively dealt with using the current generation of supercomputers. In fact, due to their size and complexity, these problems are often very numerically and/or data intensive and consequently require a variety of heterogeneous resources that are not available on a single machine Grid computing is the next logical step in distributed networking. Just as the Internet allows users to share ideas and files as the seeds of projects, grid computing lets us share the resources of disparate computer systems.
The major purpose of a grid, is to visualize resources to solve problems. So, rather than using a network of computers simply to communicate and transfer data, The grid computing helps in exploiting underutilized resources, achieving parallel CPU capacity; provide virtual resources for collaboration and reliability.
This new approach is known by several names, such as meta computing, scalable computing, global computing, Internet computing, and more recently peer-to-peer or Grid computing. Grid computing used for Those problems that are beyond the processing limits of individual computers. Right now that primarily means scientific or technical projects such as cancer and other medical research -- projects that involve the analysis of inordinate amounts of data.
Some examples of current uses of grid computing Perhaps the most ambitious is Oxford University's Centre for Computational Drug Discovery's project that utilizes more than one million PCs to look for a cancer cure. People around the world donate a few CPU cycles from their PCs through "screensaver time." The project eventually will analyze 3.5 billion molecules for cancer-fighting potential. More than 50,000 years of CPU power (based on a 1.5 gigahertz chip) have been put to work so far.
One highly publicized project is the SETI (Search for Extraterrestrial Intelligence) @Home project, in which PC users worldwide donate unused processor cycles to help the search for signs of extraterrestrial life by analyzing signals coming from outer space The five big ideas behind grid computing
1. Resource sharing on a global scale: Sharing is the very essence of grid computing. 2. Secure access: There must be a high level of trust between resource providers and users, who often don't know each other. Sharing resources is fundamentally in conflict with the conservative security policies being applied at individual computer centers and on individual PCs. So getting grid security right is crucial. 3. Resource use : Demand for grid resources should be balanced, so that computers everywhere are used more efficiently.
4. The death of distance: For grids to work, we need to ensure that distance makes no difference to efficient access to computer resources. 5. Open standards : Open standards are needed to ensure that grids are interoperable and that everyone can contribute constructively to grid development. Standardization also encourages industry to invest in developing commercial grid services and infrastructure The basics
Grid computing joins together many individual computers, creating a large system with massive computational power that far surpasses the power of a handful of supercomputers. Because the work is split into small pieces that can be processed simultaneously, research time is reduced from years to months. The technology is also more cost-effective, enabling better use of critical funds How it works
In the global grid computing scenario, unused processing power on local clusters of computers scattered across the Internet would be harnessed to address a single, complex application. Grid computing works by distributing computational resources but maintaining central control of the process. A central server acts as a team leader and traffic monitor.
This controlling cluster server divides a task into subtasks, then assigns the work to computers with surplus processing power on the grid. It also monitors the processing and, if the subtask routine fails, it will restart or reassign it. When all the subtasks have been completed, the controlling cluster server aggregates the results and advances to the next task until the whole job is completed.
In a grid campus, a hierarchical structure of many grid servers may handle subtasks, but all processing occurs on a single network. In a global grid, machines can be on many different networks and on the Web. Because they're processing in so many different circumstances, network latency can be a problem. But before any processing can occur, available resources must be identified and located. Access to them must be negotiated, and the hardware and software must be configured to effectively use the resources, which often are many smaller computers
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Concerns about grid computing Whenever you link two or more computers together, you have to prepare yourself for certain questions. How do you keep personal information private? How do you protect the system from malicious hackers? How do you control who can access the system and use its resources? How do you make sure the user doesn't tie up all the system resource? The short answer to this question is middleware. There's nothing inherent in a grid computing system that can answer these questions.
The emerging protocols for grid computing systems are designed to make it easier for developers to create applications and to facilitate communication between computers. The most prevalent technique computer engineers use to protect data is encryption. To encrypt data is to encode it so that only someone possessing the appropriate key can decode the data and access it. Ironically, a hacker could conceivably create a grid computing system for the purpose of cracking encrypted information.
Because encryption techniques use complicated to encode data, it would take a normal computer several years to crack a code (which usually involves finding the two largest prime divisors of an incredibly large number). With a powerful enough grid computing system, a hacker might find a way to reduce the time it takes to decipher encrypted data. It's hard to protect a system from hackers, particularly if the system relies on open standards. Every computer in a grid computing system has to have specific software to be able to connect and interact with the system as a whole -- computers don't know how to do it on their own. If the computer system's software is proprietary, it might be harder (but not impossible) for a hacker to access the system.
In most grid computing systems, only certain users are authorized to access the full capabilities of the network. Otherwise, the control node would be flooded with processing requests and nothing would happen (a situation called deadlock in the IT business). It's also important to limit access for security purposes. For that reason, most systems have authorization and authentication protocols. These protocols limit network access to a select number of users. Other users are still able to access their own machines, but they can't leverage the entire network. The middleware and control node of a grid computing system are responsible for keeping the system running smoothly.
Together, they control how much access each computer has to the network's resources and vice versa. While it's important not to let any one computer dominate the network, it's just as important not to let network applications take up all the resources of any one computer. If the system robs users of computing resources, it's not an efficient system. Conclusion: Grid computers stand to be the new era of computers. Grid computing made solving tasks of computers play easy. Its like "With a million people you can create a road in one day, one worker needs a million days to do the same."