Data Center Resource Provisioning Using Particle Swarm Optimization and Cuckoo Search: A Performance Comparison

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Abstract

The major concerns of cloud providers is resource management. A wide range of approaches and tools have been proposed such as meta-heuristics. Among the most recent suggested meta-heuristics are: Cuckoo Search (CS) and Particle Swarm Optimization (PSO). The main contribution of this paper is to compare the performance of CS and PSO on the resource allocation in a data center. Extensive simulation, using a dataset varying from the range of 200 to 1000 demands, demonstrates that PSO converges most rapidly than CS. Moreover, the results show an enhancement of as much as 1% to 10% of energy consumption and 1% to 5% of resource utilization on average.

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Braiki, K., & Youssef, H. (2020). Data Center Resource Provisioning Using Particle Swarm Optimization and Cuckoo Search: A Performance Comparison. In Advances in Intelligent Systems and Computing (Vol. 1151 AISC, pp. 1138–1149). Springer. https://doi.org/10.1007/978-3-030-44041-1_98

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