Wen-Juan Fan, Shan-Lin Yang, Harry Perros and Jun Pei. A Multi-dimensional Trust-aware Cloud Service Selection Mechanism Based on Evidential Reasoning Approach. International Journal of Automation and Computing, vol. 12, no. 2, pp. 208-219, 2015. https://doi.org/10.1007/s11633-014-0840-3
Citation: Wen-Juan Fan, Shan-Lin Yang, Harry Perros and Jun Pei. A Multi-dimensional Trust-aware Cloud Service Selection Mechanism Based on Evidential Reasoning Approach. International Journal of Automation and Computing, vol. 12, no. 2, pp. 208-219, 2015. https://doi.org/10.1007/s11633-014-0840-3

A Multi-dimensional Trust-aware Cloud Service Selection Mechanism Based on Evidential Reasoning Approach

doi: 10.1007/s11633-014-0840-3
Funds:

This work was supported by National Natural Science Foundation of China (Nos. 71131002, 71071045, 71231004 and 71201042).

  • Received Date: 2013-03-26
  • Rev Recd Date: 2014-03-13
  • Publish Date: 2015-04-01
  • In the last few years, cloud computing as a new computing paradigm has gone through significant development, but it is also facing many problems. One of them is the cloud service selection problem. As increasingly boosting cloud services are offered through the internet and some of them may be not reliable or even malicious, how to select trustworthy cloud services for cloud users is a big challenge. In this paper, we propose a multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning (ER) approach that integrates both perception-based trust value and reputation based trust value, which are derived from direct and indirect trust evidence respectively, to identify trustworthy services. Here, multi-dimensional trust evidence, which reflects the trustworthiness of cloud services from different aspects, is elicited in the form of historical users' feedback ratings. Then, the ER approach is applied to aggregate the multi-dimensional trust ratings to obtain the real-time trust value and select the most trustworthy cloud service of certain type for the active users. Finally, the fresh feedback from the active users will update the trust evidence for other service users in the future.

     

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