Journal
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
Volume 23, Issue 4, Pages 2871-2889Publisher
SPRINGER
DOI: 10.1007/s10586-020-03053-x
Keywords
Cloud computing; Dynamic resource allocation; Makespan; Cost; Task scheduling
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The dynamic resource allocation is a good feature of the cloud computing environment. However, it faces serious problems in terms of service quality, fault tolerance, and energy consumption. It was necessary, then, to find an effective method that can effectively address these important issues and increase cloud performance. This paper presents a dynamic resource allocation model that can meet customer demand for resources with improved and faster responsiveness. It also proposes a multi-objective search algorithm called Spacing Multi-Objective Antlion algorithm (S-MOAL) to minimize both the makespan and the cost of using virtual machines. In addition, its impact on fault tolerance and energy consumption was studied. The simulation revealed that our method performed better than the PBACO, DCLCA, DSOS and MOGA algorithms, especially in terms of makespan.
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