Cooperativeness prediction in P2P networks

Cooperativeness prediction in P2P networks
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P2P网络中的合作性预测

DOI:
10.1016/j.eswa.2007.08.046
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发表时间:
2008-10
影响因子:
8.5
通讯作者:
Heng Luo
Heng Luo
中科院分区:
计算机科学1区
文献类型:
--
作者:
Liping Shen;Jian Wang;Changyong Niu;Ruimin Shen;Heng Luo

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Peer-to-peer systems are open communities, in which not only is there no overarching control, but neither is there any hierarchy of control among the system components. In such open communities where peers can join and leave freely and behave autonomously, selecting appropriate peers to cooperate with is a challenging problem, since the candidate peers may be unreliable or dishonest. Reputation systems have been proposed to boost trust and enhance collaboration among peers. However, conventional computational reputation systems tend to generate trust based on ad hoc aggregation techniques thus produce reputation values with ambiguous meanings. In this paper we propose a probabilistic computational approach to model and generate reputation. By explicitly separating the reputation between providing services and giving recommendations, our solution represents the estimate of service quality for a specific transaction as a probability conditioned upon each retrieved recommendation, thus taking the innate behaviours of reporters into account. A Kalman filter is applied to learn further the service reputation from the estimate. The proposed approach works well even when there is sparse feedback from the reporting peers giving output with well-defined semantics and useful meanings.
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