Novel Technique for Atomic Web Services Reliability for Service Oriented Architecture

Abstract

To address the challenges in prediction of atomic web service reliability for the Service Oriented Architecture (SOA), in this paper we proposed the clustering based approach called the Dynamic Clustering (DCLUS). The DCLUS is based on recent work reported called CLUS. The novelty in DCLUS compared to CLUS technique is use of dynamic width clustering technique. In CLUS, k-means clustering method exploited for the users and services clustering. However, due to the limitations of k-means, the dynamic width clustering is proposed to optimize the performance of clustering and hence the prediction accuracy. The proposed DCLUS model for the reliability prediction of atomic web services that estimates the reliability for an ongoing service invocation based on the data assembled from previous invocations. With the aim to improve the accuracy of the current state-of-the-art prediction models, we incorporate user–, service– and environment–specific parameters of the invocation context