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Cloud computing resources scheduling optimisation based on improved bat algorithm via wavelet perturbations

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.