DocumentCode :
1788528
Title :
A trust and reputation management system for cloud and sensor networks integration
Author :
Chunsheng Zhu ; Nicanfar, Hasen ; Leung, Victor C. M. ; Wenxiang Li ; Yang, L.T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada
fYear :
2014
fDate :
10-14 June 2014
Firstpage :
557
Lastpage :
562
Abstract :
By incorporating the advantages of cloud computing (CC) and wireless sensor networks (WSNs), the integration of CC and WSNs attracts a lot of attention from both academia and industry. However, trust and reputation management for CC and WSNs integration is a critical and barely explored issue, which could strongly prevent the cloud service users (CSUs) from choosing the desirable cloud service providers (CSPs) or hinder the CSP from selecting appropriate sensor network providers (SNPs). To fill the gap, this paper proposes a novel trust and reputation management system for CC and WSNs integration. Considering the attribute requirement of CSU and CSP as well as the cost, trust and reputation of the service of CSP and SNP, the proposed system achieves the following two goals: 1) calculate and manage the trust and reputation regarding the service of CSP and SNP; 2) help CSU choose CSP and assist CSP in choosing SNP. Evaluation results are also shown to verify effectiveness of the proposed system.
Keywords :
cloud computing; wireless sensor networks; CC; CSPs; CSUs; SNPs; WSNs; cloud computing; cloud service providers; cloud service users; reputation management system; sensor network providers; trust management system; wireless sensor networks; Ad hoc networks; Cloud computing; Clouds; Digital signal processing; Educational institutions; Servers; Wireless sensor networks; Cloud; integration; reputation; sensor networks; trust;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (ICC), 2014 IEEE International Conference on
Conference_Location :
Sydney, NSW
Type :
conf
DOI :
10.1109/ICC.2014.6883377
Filename :
6883377
Link To Document :
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