BAT and Hybrid BAT Meta-Heuristic for Quality of Service-Based Web Service Selection

Podili, P and Pattanaik, K K and Rana, P S (2017) BAT and Hybrid BAT Meta-Heuristic for Quality of Service-Based Web Service Selection. Journal of Intelligent Systems, 26 (1). pp. 123-137. ISSN 0334-1860

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Efficient QoS-based service selection from a pool of functionally substitutable web services (WS) for constructing composite WS is important for an efficient business process. Service composition based on diverse QoS requirements is a multi-objective optimization problem. Meta-heuristic techniques such as genetic algorithm (GA), particle swarm optimization (PSO), and variants of PSO have been extensively used for solving multi-objective optimization problems. The efficiency of any such meta-heuristic techniques lies with their rate of convergence and execution time. This article evaluates the efficiency of BAT and Hybrid BAT algorithms against the existing GA and Discrete PSO techniques in the context of service selection problems. The proposed algorithms are tested on the QWS data set to select the best fit services in terms of maximum aggregated end-to-end QoS parameters. Hybrid BAT is found to be efficient for service composition.

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Item Type: Article
Uncontrolled Keywords: Web service; composition; meta-heuristic; particle swarm optimization (PSO); BAT algorithm; Hybrid BAT algorithm
Subjects: Computer science > Big Data Analytics
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 27 Jan 2016 04:53
Last Modified: 23 Jan 2017 04:32
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