Title: Cloud computing resources scheduling optimisation based on improved bat algorithm via wavelet perturbations
Authors: Yan Zhang; Zhaobin Liu; Fahong Yu; Tao Jiang
Addresses: Department of Computer Engineering, Suzhou Vocational University, Suzhou, China ' Department of Computer Engineering, Suzhou Vocational University, Suzhou, China ' College of Mathematics and Information Engineering, Jiaxing University, Zhejiang, China; Ningbo Institute of Technology, Zhejiang University, Ningbo, China ' College of Mathematics and Information Engineering, Jiaxing University, Zhejiang, China; Ningbo Institute of Technology, Zhejiang University, Ningbo, China
Abstract: Efficient scheduling of computing resources is a fundamental issue that the cloud computing needs to solve, which involves highly challenging load-balance of multiple computing resources. In order to achieve optimal balance between the executing speed, the average response time and the overall system utilisation during cloud computing resource allocation, a cloud computing resources scheduling optimisation algorithm is proposed based on wavelet perturbation-based bat algorithm (WPBA). The algorithm first employs wavelet perturbation to enhance Bat algorithm's performance followed by population-entropy-guided substitution to control diversity and improve the converging speed and accuracy. Then it adopts WPBA to achieve resources scheduling optimisation of the cloud computing. The experiment shows that using WPBA has significantly improved the overall performance of the algorithm and has also remarkably optimised the resource scheduling capability of cloud computing and heightened the overall resource utilisation.
Keywords: cloud computing; resource dispatch; swarm intelligence; improved bat algorithm.
International Journal of High Performance Systems Architecture, 2017 Vol.7 No.4, pp.189 - 196
Available online: 05 Jun 2018 *Full-text access for editors Access for subscribers Purchase this article Comment on this article