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TrustyFeer: A Subjective Logic Trust Model for Smart City Peer-to-Peer Federated Clouds

Author(s)
Alshayban, Bushra; Altoaimy, Lina; Alsalamah, Shada; Kurdi, Heba A.
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Abstract
Cloud computing plays a major role in smart cities development by facilitating the delivery of various services in an efficient and effective manner. In a Peer-to-Peer (P2P) federated clouds ecosystem, multiple Cloud Service Providers (CSPs) collaborate and share services among them when experiencing a shortage in certain resources. Hence, incoming service requests to this specific resource can be delegated to other members. Nevertheless, the lack of preexisting trust relationship among CSPs in this distributed environment can affect the quality of service (QoS). Therefore, a trust management system is required to assist trustworthy peers in seeking reliable communication partners. We address this challenge by proposing TrustyFeer, a trust management system that allows peers to evaluate the trustworthiness of other peers based on subjective logic opinions, formulated using peers’ reputations and Service Level Agreements (SLAs). To demonstrate the utility of TrustyFeer, we evaluate the performance of our method against two long-standing trust management systems. The simulation results show that TrustyFeer is more robust in decreasing the percentage of services that do not conform to SLAs and increasing the success rate of exchanged services by good CSPs conforming to SLAs. This should provide a trustworthy federated clouds ecosystem for a better, more sustainable future.
Date issued
2018-02
URI
http://hdl.handle.net/1721.1/114842
Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics; Massachusetts Institute of Technology. Department of Mechanical Engineering
Journal
Wireless Communications and Mobile Computing
Publisher
Hindawi Publishing Corporation
Citation
Kurdi, Heba, et al. “TrustyFeer: A Subjective Logic Trust Model for Smart City Peer-to-Peer Federated Clouds.” Wireless Communications and Mobile Computing, vol. 2018, 2018, pp. 1–13. © 2018 Heba Kurdi et al.
Version: Final published version
ISSN
1530-8669
1530-8677

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