Title: An efficient resource deployment method for stream-based stochastic demands in distributed cloud platforms

Authors: Yang Liu; Wei Wei; Heyang Xu

Addresses: College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China ' College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China ' College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China

Abstract: It has been a consensus that deploying geographically dispersed stream-based online services into distributed cloud platforms has gained exceptional advantages. Globally visiting services make user requests characterised with dramatic fluctuation, which introduces stochastic demands for various resources. In order to maximise satisfied user requests and guarantee quality-of-service under given expense budget, efficient resource deployment becomes the key to this problem. We propose a stochastic demand oriented resource deployment method with more profits and less time complexity. Experiments using simulated and realistic data indicate that proposed method can outperform existing algorithms by increasing the weighted summation of satisfied demands up to 37%, fit for all scenarios with heterogeneous distributed cloud resources.

Keywords: resource deployment; differential evolution; stochastic demand; heterogeneous clouds.

DOI: 10.1504/IJCSM.2020.111703

International Journal of Computing Science and Mathematics, 2020 Vol.12 No.3, pp.205 - 215

Received: 23 Apr 2018
Accepted: 04 Sep 2018
Published online: 11 Dec 2020 *

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