Title: Using seagull optimisation algorithm to select mobile service in cloud and edge computing environment

Authors: Feilong Yu; Jing Li; Ming Zhu; Xiukun Yan

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: With the rapid development of edge computing, more and more services are deployed on edge servers. Compared with traditional cloud computing, services in the edge computing environment are closer to users, which bring benefits of high performance and low latency to the user-service interactions. However, due to the limited resources of edges, services provided by edges alone may fail to meet increasingly complex mobile computing requirements; therefore, services on clouds become an effective supplement. With the massive increment of services in the mobile internet, selecting proper services to fulfil mobile users' requests becomes a key research field. This paper proposes a service selection model for mobile service selection problem in cloud and edge computing environment. The proposed model combines the seagull optimisation algorithm and the simulated annealing algorithm. Through comparative experiments on simulation datasets with referencing to some other service selection models, it can be inferred that the proposed selection model finds a solution with better QoS performance in fewer iterations.

Keywords: mobile edge computing; cloud computing; seagull optimisation algorithm; SOA; service selection.

DOI: 10.1504/IJWET.2022.10049995

International Journal of Web Engineering and Technology, 2022 Vol.17 No.1, pp.88 - 114

Received: 13 Oct 2021
Received in revised form: 03 May 2022
Accepted: 09 May 2022

Published online: 25 Aug 2022 *

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