Grid computing solves larger scale applications by coordinating and sharing computational power, data storage and network resources across dynamic and geographically dispersed organizations by providing high performance computing platform with the goal of providing users with access to the resources they need, even when they need. Grids provide remote access to IT assets, and aggregate processing power. The goal of scheduling is to achieve highest possible system throughput and to match the application need with the available computing resources. Scheduling onto the Grid is NP complete, so there is no best scheduling algorithm for all grid computing systems. The basic grid model generally composed of a number of hosts, each composed of several computational resources, which may be homogeneous or heterogeneous. In this article we have discussed all possible job scheduling algorithm in brief and lastly provided comparison for all.

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Grid Computing Job Scheduling Scheduling Algorithm