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The Journal of Supercomputing

, Volume 73, Issue 10, pp 4535–4559 | Cite as

A rough set-based hypergraph trust measure parameter selection technique for cloud service selection

  • Nivethitha Somu
  • Kannan Kirthivasan
  • V. S. Shankar SriramEmail author
Article

Abstract

Selection of trustworthy cloud services has been a major research challenge in cloud computing, due to the proliferation of numerous cloud service providers (CSPs) along every dimension of computing. This scenario makes it hard for the cloud users to identify an appropriate CSP based on their unique quality of service (QoS) requirements. A generic solution to the problem of cloud service selection can be formulated in terms of trust assessment. However, the accuracy of the trust value depends on the optimality of the service-specific trust measure parameters (TMPs) subset. This paper presents TrustCom—a novel trust assessment framework and rough set-based hypergraph technique (RSHT) for the identification of the optimal TMP subset. Experiments using Cloud Armor and synthetic trust feedback datasets show the prominence of RSHT over the existing feature selection techniques. The performance of RSHT was analyzed using Weka tool and hypergraph-based computational model with respect to the reduct size, time complexity and service ranking.

Keywords

Cloud service providers (CSPs) Cloud users (CUs) Trust measure parameters (TMPs) Rough set theory (RST) Hypergraph Hypergraph-based computational model (HGCM) 

Notes

Acknowledgements

The first and third author thanks the Department of Science and Technology, New Delhi, India, for INSPIRE Fellowship (Grant No: DST/INSPIRE Fellowship/2013/963) and Fund for Improvement of S&T Infrastructure in Universities and Higher Educational Institutions (SR/FST/ETI-349/2013) for their financial support. The second author thanks the Department of Science and Technology, New Delhi, India—Fund for Improvement of S&T Infrastructure in Universities and Higher Educational Institutions Government of India (SR/FST/MSI-107/2015) for their financial support.

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Centre for Information Super Highway (CISH), School of ComputingSASTRA UniversityThanjavurIndia
  2. 2.Discrete Mathematics Research Laboratory (DMRL), Department of MathematicsSASTRA UniversityThanjavurIndia

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