Title: A service selection method in mobile edge and cloud environment based on skyline and cuckoo optimisation algorithm

Authors: Xiukun Yan; Ming Zhu; Jing Li; Jinling Zhao

Addresses: College of Computer Science and Technology, Shandong University of Technology, Zibo, China ' College of Computer Science and Technology, Shandong University of Technology, Zibo, China ' College of Computer Science and Technology, Shandong University of Technology, Zibo, China ' College of Computer Science and Technology, Shandong University of Technology, Zibo, China

Abstract: Compared with traditional cloud computing, services provided by edge computing have several advantages such as high speed and low latency, which make edge services become the key technology of 5G. However, the number of edge servers, the computing capability of an edge server and the number of services deployed on an edge server are limited. Therefore, researchers propose to combine edge computing with cloud computing. How to select appropriate cloud and edge services with low response time and cost to meet complex needs of mobile users is a NP-hard problem. To solve the problem, in this paper, we propose a mobile service selection method in an edge and cloud computing environment based on the combination of skyline and cuckoo optimisation algorithm. Firstly, the skyline method is used to pre-process candidate services and filter out services with poor quality. Secondly, by modelling the mobility of user and the service composition pattern, the cuckoo optimisation algorithm is utilised to select proper edge and cloud services to fulfil user's requirements. To verify the effectiveness and efficiency of the proposed method, experiments are carried out and results indicate that the proposed method has better performance than the referred state-of-art methods.

Keywords: edge computing; cloud computing; service selection; skyline; cuckoo optimisation algorithm; COA.

DOI: 10.1504/IJWGS.2022.126125

International Journal of Web and Grid Services, 2022 Vol.18 No.4, pp.453 - 478

Received: 20 Jan 2022
Received in revised form: 20 May 2022
Accepted: 30 May 2022
Published online: 11 Oct 2022 *

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