Abstract
Grid computing is a high performance computing environment that allows sharing of geographically distributed resources across multiple administrative domains serving the ever growing demand for computational power. Scheduling m jobs to n resources to optimise the QoS for the given objective parameters has been proven to be NP-complete. This work presents two centralised level based batch scheduling strategies for a computational grid with the objective of minimising the turnaround time. The scheduler evaluates various computational nodes to schedule the batch of jobs consisting of a number of sub-jobs/modules having precedence and dependence constraints along with inter module communication requirements. Minimum Completion Time MCT and Minimum Execution Time MET heuristics have been used to decide the most suitable node for the given sub-job in terms of the turnaround time offered. A comparative analysis of the strategies with a model with similar objective has been performed to evaluate their place in the middleware.
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