| Summary: | Grid computing is a form of distributed computing that involves coordinating and sharing computing, application, data storage or network resources across dynamic and geographically dispersed organizations. Today scheduling in Grid computing involves much static and fix algorithm. Research on Grid scheduling focuses in solving three problems: finding a good algorithm, automating the process, and building a flexible, scalable, and efficient scheduling mechanism. The complexity of scheduling problem increases with the size of the Grid. The goal of this project is to test on tardiness parameter in local search based algorithms. A good scheduling algorithm normally shows lower value of total tardiness and schedule time. In this project, the comparisons of scheduling techniques were done in simulation Grid. The implementation was tested and evaluated on universal datasets using GridSim 4.1. Tabu Search has been selected for its efficiency in distributing jobs. The result shows that the performance of tardiness is directly related to the number of machines up to certain number of resources. Small and medium company can use grid in operation process because it saves cost and time.
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