Title: Mobile service selection in edge and cloud computing environment with grey wolf algorithm

Authors: Ming Zhu; Siyuan Meng; Jing Li; Song Yan

Addresses: College of Computer Science and Technology, Shandong University of Technology, Zibo, China ' College of Computer Science and Technology, East China Nromal University, Shanghai, China ' College of Computer Science and Technology, Shandong University of Technology, Zibo, China ' College of Data Science and Engineering, East China Normal University, Shanghai, China

Abstract: The proliferation of mobile devices has resulted in the tremendous development of edge computing. A common mechanism is that once the requests from the users are too complex to be afforded by a single service, then edge computing services ought to step in. Nevertheless, services on edge servers are most commonly resource-constrained and unstable. To this end, we propose a novel solution for the mobile service selection problem with edge and cloud computing. An extended grey wolf algorithm is presented; specifically, crossover operator and roulette wheel are applied in reproduction and selection operations. Comparative experiments are implemented between our approach and other nature-inspired algorithms to verify the effectiveness and efficiency, which demonstrate our method may find a solution with better QoS values.

Keywords: mobile edge computing; cloud computing; grey wolf algorithm; quality of services; QoSs; service selection.

DOI: 10.1504/IJWGS.2022.123680

International Journal of Web and Grid Services, 2022 Vol.18 No.3, pp.229 - 249

Received: 17 Jun 2021
Accepted: 28 Sep 2021
Published online: 30 Jun 2022 *

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