Title: Towards the optimality of QoS-aware web service composition with uncertainty

Authors: Sen Niu; Guobing Zou; Yanglan Gan; Yang Xiang; Bofeng Zhang

Addresses: School of Computer and Information Engineering Shanghai Polytechnic University, Shanghai, China; School of Computer Engineering and Science, Shanghai University, Shanghai, 200444, China ' School of Computer Engineering and Science, Shanghai University, Shanghai, 200444, China ' School of Computer Science and Technology, Donghua University, Shanghai, 201620, China ' School of Computer Engineering and Science, Shanghai University, Shanghai, 200444, China ' School of Computer Engineering and Science, Shanghai University, Shanghai, 200444, China

Abstract: Quality of service (QoS)-aware web service composition (QWSC) has recently become one of the most challenging research issues. Although much work has been investigated, they mainly focus on certain QoS of web services, while QoS with uncertainty exposes the most important characteristic in real and highly dynamic environment. In this paper, with the consideration of uncertain service QoS and user's preferences, we model the issue of uncertain QoS-aware WSC via interval number and translate it into a multi-objective optimisation problem with global QoS constraints of user's preferences. The encoded optimisation problem is solved by an non-deterministic multi-objective evolutionary algorithm, which exploits new genetic encoding schema, the strategy of crossover and uncertain interval Pareto comparison. To validate the feasibility, large-scale experiments have been conducted on simulated datasets. The results demonstrate that our proposed approach can effectively and efficiently find optimum composite service solutions set with satisfactory convergence.

Keywords: web services; uncertain QoS; WSC; web service composition; multi-objective optimisation.

DOI: 10.1504/IJWGS.2019.10017534

International Journal of Web and Grid Services, 2019 Vol.15 No.1, pp.1 - 28

Received: 07 Oct 2017
Accepted: 02 Feb 2018

Published online: 26 Nov 2018 *

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