Grid computing made simple

There has been a surge of interest in grid computing, a way to enlist large numbers of machines to work on multipart computational problems such as circuit analysis or mechanical design. There are excellent reasons for this attention among scientists, engineers, and business executives. 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 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. The term grid, however, may mean different things to different people. To some users, a grid is any network of machines, including personal or desktop computers within an organization. To others, grids are networks that include computer clusters, clusters of clusters, or special data sources. Both of these definitions reflect a desire to take advantage of vastly powerful but inexpensive networked resources. In our work, we focus on the use of grids to perform computations as opposed to accessing data, another important are known as data grid research.