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Hybrid Metaheuristics Web Service Composition Model for QoS Aware Services

P. Rajeswari*, K. Jayashree

Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, 602105, India

* Corresponding Author: P. Rajeswari. Email: email

Computer Systems Science and Engineering 2022, 41(2), 511-524. https://doi.org/10.32604/csse.2022.020352

Abstract

Recent advancements in cloud computing (CC) technologies signified that several distinct web services are presently developed and exist at the cloud data centre. Currently, web service composition gains maximum attention among researchers due to its significance in real-time applications. Quality of Service (QoS) aware service composition concerned regarding the election of candidate services with the maximization of the whole QoS. But these models have failed to handle the uncertainties of QoS. The resulting QoS of composite service identified by the clients become unstable and subject to risks of failing composition by end-users. On the other hand, trip planning is an essential technique in supporting digital map services. It aims to determine a set of location based services (LBS) which cover all client intended activities quantified in the query. But the available web service composition solutions do not consider the complicated spatio-temporal features. For resolving this issue, this study develops a new hybridization of the firefly optimization algorithm with fuzzy logic based web service composition model (F3L-WSCM) in a cloud environment for location awareness. The presented F3L-WSCM model involves a discovery module which enables the client to provide a query related to trip planning such as flight booking, hotels, car rentals, etc. At the next stage, the firefly algorithm is applied to generate composition plans to minimize the number of composition plans. Followed by, the fuzzy subtractive clustering (FSC) will select the best composition plan from the available composite plans. Besides, the presented F3L-WSCM model involves four input QoS parameters namely service cost, service availability, service response time, and user rating. An extensive experimental analysis takes place on CloudSim tool and exhibit the superior performance of the presented F3L-WSCM model in terms of accuracy, execution time, and efficiency.

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APA Style
Rajeswari, P., Jayashree, K. (2022). Hybrid metaheuristics web service composition model for qos aware services. Computer Systems Science and Engineering, 41(2), 511-524. https://doi.org/10.32604/csse.2022.020352
Vancouver Style
Rajeswari P, Jayashree K. Hybrid metaheuristics web service composition model for qos aware services. Comput Syst Sci Eng. 2022;41(2):511-524 https://doi.org/10.32604/csse.2022.020352
IEEE Style
P. Rajeswari and K. Jayashree, "Hybrid Metaheuristics Web Service Composition Model for QoS Aware Services," Comput. Syst. Sci. Eng., vol. 41, no. 2, pp. 511-524. 2022. https://doi.org/10.32604/csse.2022.020352



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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