GRID AND DISTRIBUTED NETWORK TO HANDLE MAMMOTH TASKS

d hardware and software resources” [1] In 2001, Foster, Kesselman and Tuecke refined their definition of a Grid to “coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations” [2]. This latest definition is the one most commonly used today to abstractly define a Grid. Half a decade ago, Ian Foster later produced a checklist with three parts [3] that helps to understand exactly what can be identified as a Grid system. The first part to check off is that there is coordinated resource sharing with no centralized point of control that the users reside within different administrative domains. If this is not true, probably this is not a Grid system.

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    Grid and Distributed Networks to handle mammoth tasks
    (2013-10-01T04:30:46Z) KAMATH, RADHIKA
    To analyze huge data sets instantaneously, run scenarios thousands of times, to get the results after operations always faster, accurate, with an increase in productivity the super computers can be used. But what if the same mammoth tasks can be achieved through the IT components the user already own? Mainframes, servers, databases, storage systems, desktop computers and workstations can be pulled together to realize this power of a super computer, through Grid and Distributed Computing. Grid provides a collection of servers, clients and other resources often working collectively together to solve a problem. Much of Grid and distributed software technology addresses the issues of resource scheduling, quality of service, fault tolerance, decentralized control and security and so on. Grids are intrinsically distributed and heterogeneous, but must be perceived by the user as a single virtual platform or environment with uniform access to the resources. The large and complex system of Grid software has to be robust, useful and provide an interoperable collection of services that support large-scale distributed computing and data management. Perspective of this paper provides a comprehensive look at the state of the art and best practices for wide areas of Grid and Distributed Computing.