Cloud Service Composition Based on Multi-Granularity Clustering

• Main Authors: Huihui Cai, Lizhen Cui
• Format: Article
• Language: English
• Published: SAGE Publishing 2014-06-01
• Series: Journal of Algorithms & Computational Technology
• Online Access: https://doi.org/10.1260/1748-3018.8.2.143

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.