Cloud Service Composition Based on Multi-Granularity Clustering. Issue 2 (June 2014)

• Record Type: Journal Article
• Authors: Cai, Huihui; Cui, Lizhen
• Is Part Of: Journal of algorithms & computational technology. Volume 8:Issue 2(2014)
• Page Start: 143
• Page End: 161
• Publication Date: 2014-06
• Subjects: cloud computing -- service composition -- multi-granularity clustering -- correlation mining; Computer algorithms -- Periodicals; Numerical calculations -- Periodicals; Computer algorithms; Numerical calculations; Periodicals; 518.1
• DOI: 10.1260/1748-3018.8.2.143
• Languages: English
• ISSNs: 1748-3018

Abstract

With the popularity of cloud computing, how to meet user's personalized and diverse requirements of service composition is a key problem that needs to be resolved. This paper proposes a cloud service composition method based on multi-granularity clustering, organizing services in the perspective of granularity to meet user's such requirements in service composition. Services disorder turn to be in order through multi-granularity clustering, which includes three steps: basic services clustering based on message semantic similarity computing, correlation mining and multi-granularity services clustering. The experimental results demonstrate that by utilizing the proposed method, users' personalized and diverse requirements are satisfied and the efficiency of service composition is improved greatly.