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Optimized Web Service Composition Using Evolutionary Computation Techniques

Publication Type : Conference Paper

Publisher : Springer

Source : Lecture Notes on Data Engineering and Communications Technologies, vol 57. Springer, Singapore. https://doi.org/10.1007/978-981-15-9509-7_38

Url : https://link.springer.com/chapter/10.1007/978-981-15-9509-7_38

Campus : Amritapuri

School : School of Computing

Year : 2022

Abstract : In service computing, Quality of Service (QoS)-aware web service composition is considered as one of the influential traits. To embrace this, an optimal method for predicting QoS values of web service is implemented where credibility evaluation is computed by accumulating reputation and trustworthiness. An automatic approach for weight calculation is invoked to calculate the weight of QoS attributes; it improves WS QoS values. QoS value is optimized by using Genetic Algorithm. Services with high QoS values are taken as candidate services for service composition. Instead of just selecting services randomly for service composition, cuckoo-based algorithm is used to identify optimal web service combination. Cuckoo algorithm realizes promising combinations by replacing the best service in lieu of worst service and by calculating the fitness score of each composition. A comparative study proved that it can provide the best service to end-users, as cuckoo selects only service composition with high fitness score.

Cite this Research Publication : Subbulakshmi, S., Ramar, K., Saji, A.E., Chandran, G. (2021), "Optimized Web Service Composition Using Evolutionary Computation Techniques," In: Hemanth, J., Bestak, R., Chen, J.IZ. (eds) Intelligent Data Communication Technologies and Internet of Things. Lecture Notes on Data Engineering and Communications Technologies, vol 57. Springer, Singapore. https://doi.org/10.1007/978-981-15-9509-7_38

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