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.
Highlights
With the developments of Cloud Computing (CC) and Software as a Service (SaaS), an increased applications and processing resources have been summarized as Web Services (WSs) and provided on the web [1]
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
A series of simulations were performed on benchmark dataset to demonstrate the promising results of the F3L-WSCM model over the existing methods
Summary
With the developments of Cloud Computing (CC) and Software as a Service (SaaS), an increased applications and processing resources have been summarized as Web Services (WSs) and provided on the web [1]. Personal trip planning has been established as commonly utilized urban computing service and assisted by digital map service suppliers like Microsoft MapPoint and Google Map. In previous years, trip planning is hot research field, which aims to search for a capable trip for the client using querying search methods, indexing, and effective data modeling with several beneficial methods. A client might have several intentional activities, and probably, they are incapable of supporting access to any individual location-based services closer to the query locations [8] With this motivation, this study focuses on the design of an effective WS composition model for location awareness. This study introduces a novel hybridization of the firefly optimization algorithm with fuzzy logic-based web service composition model (F3L-WSCM) in a CC environment for location identification.
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