Tran Cong Hung, Le Ngoc Hieu, Phan Thanh Hy, Nguyen Xuan Phi
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MMSIA: Improved Max-Min Scheduling Algorithm for Load Balancing on Cloud Computing
Cloud computing is one of the most advanced technologies in information technology, a convergence of many achievements in research and development and application of new technologies. Cloud computing has also helped to reduce the cost of small and medium enterprises based on cloud provider services. As cloud computing evolves rapidly, researching optimizations such as task execution time, completion time, responce time, and virtual machine resources (VMs) are tremendous challenges. This article proposes an MMSIA algorithm to improve the Max-Min scheduling algorithm, which improves the completion time of the requests by using the "learned learning" machine learning, by clustering size of requests and clustering utilization percent of VMs. The algorithm then assigns the largest cluster requests to the VM with the least utilization percent, which is repeated when the request list is empty. In particular, the MMSIA algorithm has improved the completion time. The simulation results show that the proposed MMSIA algorithm has improved the completion time compared to the three algorithms: Max-Min, Min-Min and Roud Robin.