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Grid computing is a form of distributed computing that involves coordinating and sharing computing, application, network resources across dynamic and geographically dispersed organizations. The primary issue associated with the efficient utilization of heterogeneous resources in a grid is grid scheduling. The main objective of Grid scheduling is to get the best optimal machine to each task, which makes scheduling a complex problem. Heuristic approach is developed to obtain optimal solution. In this paper, a Hybrid Ant Colony Optimization (HACO) scheduling algorithm is proposed. Experiments are conducted with different data series and conditions. The experimental results reveal that the proposed algorithm produces better results when compared with the existing ant algorithm.
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