Cloud computing resource scheduling based on ant colony optimization and simulated annealing algorithm

Xiongwei Liang; Chen Xu; Zhefeng Zhao; Xin Zhang; Qianqian Wu

doi:10.1117/12.2652560

20 October 2022 Cloud computing resource scheduling based on ant colony optimization and simulated annealing algorithm

Xiongwei Liang, Chen Xu, Zhefeng Zhao, Xin Zhang, Qianqian Wu

Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 123502T (2022) https://doi.org/10.1117/12.2652560
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China

Abstract

In order to improve the utilization of cloud computing resources, this paper studies cloud computing resource scheduling based on improved Ant Colony Optimization Algorithm (ACO) and Simulated annealing algorithm (SA). We apply ACO and SA to schedule the large-scale cloud computing resource data. This paper uses SA to prevent ACO falling into the local optimal solution, and accelerate the convergence speed of ACO. The experimental results show that the proposed method is more effective compared with the already existed approaches. Our proposed method can improve the resource utilization.

Citation Download Citation

Xiongwei Liang, Chen Xu, Zhefeng Zhao, Xin Zhang, and Qianqian Wu "Cloud computing resource scheduling based on ant colony optimization and simulated annealing algorithm", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 123502T (20 October 2022); https://doi.org/10.1117/12.2652560

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