EFFICIENT SERVICE DISCOVERY USING HYBRID RANKING

Author (s) : J.Sowmya and S.Iswarya

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Abstract :
In current scenario, industries and organizations implement their business processes using web services. The web service should be selected from collection of compliant services using service discovery based on functional and non-functional requirements. This is still a challenging issue. In contemporary service discovery methodologies ranking, optimization and fuzzy are employed to select relatively better services. The existing Service discovery is extended to improve the service selection. The proposed system extracts system Quality QoS attribute values of all complaint service and constructs a hybrid matrix. This matrix is transformed into a fuzzy judgement matrix using fuzzy limits. The entropy weight is applied for the fuzzy matrix to select relatively best service. The empirical evaluation proves that the proposed methodology discovers the best service based on the QoS attribute values.

Keywords : Hybrid matrix, fuzzy limits, entropy weight

Conference Date : 30/08/2019

Pages : 21

Paper ID : 19020