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Title: Ontology-enhanced agent-based cloud service discovery
Authors: Jaeyong Kang; Kwang Mong Sim
School of Information and Communication, Gwangju Institute of Science and Technology, 123 Cheomdangwagi-ro, Buk-gu, Gwangju, Korea
College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
Abstract: Cloud computing has attracted great interest from both industrial and academic communities. However, only a few efforts have been devoted to building tools for supporting Cloud service discovery. Therefore, we present a four-stage, agent-based Cloud service discovery protocol. Additionally, two Cloud ontologies (CO-1 and CO-2) are designed to semantically define the relationship among Cloud services. Whereas CO-1 contains only Cloud concepts, CO-2 contains a set of Cloud concepts, individuals of those concepts, and the relationship among those individuals. The similarity among Cloud services is determined by concept, object property, and data type property similarity reasoning. In addition, two kinds of recommendation approaches (R1 and R2) based on attribute value prediction are presented. R1 is based on the maximum and R2 on the average similarity between the provided and the requested requirements. Empirical results show that our system achieved the best performance in finding the appropriate Cloud services with CO-2 and R2.
Keywords: cloud computing; cloud ontology; multi-agent systems; MAS; information retrieval; agent-based systems; cloud services; service discovery; recommendation systems; recommender systems; similarity reasoning.
Int. J. of Cloud Computing, 2016 Vol.5, No.1/2, pp.144 - 171
Date of acceptance: 15 Nov 2015
Available online: 02 Mar 2016