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Rapid growth of internet and other technologies seems more challenging to develop the high speed networks with powerful capabilities in lower computational cost. To cover the above problem grid computing has emerged rapidly. The previous technologies such as distributed computing cluster computing, parallel computing, etc., facing the problem of space utilization. Using Grid Computing technologies...
Workload information management and resource management are two key aspects in grid computing to provide the better services to grid environment users. Grid computing also faced other challenging areas like heterogeneous nature of resources, huge number of computing elements, independency of computing resources, different processing capacities of the nodes, different types of load conditions, overloading...
Grid computing is the combination of computer resources from multiple administrative domains for a common goal. Grid computing (or the use of a computational grid) is applying the resources of many computers in a network to a single problem at the same time — usually to solve a scientific or technical problem that requires a great number of computer processing cycles or access to large amounts of...
Parallel and distributed computing has been adapted to many scientific applications for aggregate computational power and memory capacity. To utilize resources efficiently and speed up application execution, tasks are split and dispatched across multiple computing elements. The ideal case is that all subtasks can finish roughly at the same time. However, this is not always achievable due to different...
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