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Title: GRID_COMPUTING
Description: GRID_COMPUTING

The popularity of the Internet as well as the availability of powerful computers and high-speed network technologies as low-cost commodity components is changing the way we use computers today. These technology opportunities have led to the possibility of using distributed computers as a single, unified computing resource, leading to what is popularly known as Grid computing.

The term Grid is chosen as an analogy to a Power Grid that provides consistent, pervasive, dependable, transparent access to electricity irrespective of its source. This new approach to network computing is known by several names, such as metacomputing, scalable computing, global computing, Internet computing, and more recently peer to peer (P2P) computing.

Grids enable the sharing, selection, and aggregation of a wide variety of resources including supercomputers, storage systems, data sources, and specialized devices that are geographically distributed and owned by different organizations for solving large-scale computational and data intensive problems in science, engineering, and commerce. Thus creating virtual organizations and enterprises as envisioned in as a temporary alliance of enterprises or organizations that come together to share resources and skills, core competencies, or resources in order to better respond to business opportunities or large-scale application processing requirements, and whose cooperation is supported by computer networks.

The concept of Grid computing started as a project to link geographically dispersed supercomputers, but now it has grown far beyond its original intent. The Grid infrastructure can benefit many applications, including collaborative engineering, data exploration, high-throughput computing, and distributed supercomputing.

A Grid can be viewed as a seamless, integrated computational and collaborative environment and a high-level view of activities within the Grid as shown in Figure. The users interact with the Grid resource broker to solve problems, which in turn performs resource discovery, scheduling, and the processing of application jobs on the distributed Grid resources. From the end-user point of view, Grids can be used to provide the following types of services.

These are concerned with proving secure access to distributed datasets and their management. To provide a scalable storage and access to the data sets, they may be replicated, catalogued, and even different datasets stored in different locations to create an illusion of mass storage. The processing of datasets is carried out using computational Grid services and such a combination is commonly called Data Grids. Sample applications that need such services for management, sharing, and processing of large datasets are high-energy physics and accessing distributed chemical databases for drug design.

Grid applications are typically developed using Grid-enabled languages and utilities such as HPC++ or MPI. An example application, such as parameter simulation or a grand-challenge problem, would require computational power, access to remote data sets, and may need to interact with scientific instruments. Grid portals offer Web-enabled application services, where users can submit and collect results for their jobs on remote resources through the Web.

There are currently a large number of projects and a diverse range of new and emerging Grid developmental approaches being pursued. These systems range from Grid frameworks to application testbeds, and from collaborative environments to batch submission mechanisms. It is difficult to predict the future in a field such as information technology where the technological advances are moving very rapidly. Hence, it is not an easy task to forecast what will become the dominant Grid approach. Windows of opportunity for ideas and products seem to open and close in the blink of an eye. However, some trends are evident. One of those is growing interest in the use of Java and Web services for network computing.

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