Refining Reputation to Truly Select High-QoS Servers in Peer-to-Peer Networks

Peer-to-peer networks (P2Ps) use reputation systems to provide incentives for nodes to offer high quality of service (QoS) and thwart the intentions of dishonest or selfish nodes. Existing reputation systems have two problems. First, they directly regard node reputation as trust. Reputation represents the opinion formed by others about a node's QoS behavior, while trust represents a node's honesty and willingness to cooperate. In addition to trust, factors such as node capacity and lifetime also influence reputation. Due to the heterogeneous and time-varying attributes of these factors, reputation actually cannot directly reflect a node's trust or current QoS. Second, existing reputation systems guide a node to select the server with the highest reputation, which may not actually select the highest QoS server and would overload the highest-reputed nodes. This work aims to accurately reflect node trust and provide accurate guidance for high QoS server selection. Through experimental study, we find that node trust, available capacity and lifetime positively affect node reputation. Based on this observation, we first propose a manual and an automatic trust model that removes the influence of additional factors on reputation to truly reflect node trust. We then propose a high-QoS server selection algorithm that separately considers node trust, current available capacity, and lifetime. Simulation results demonstrate the effectiveness of the trust models in accurate node trust reflection. Moreover, the server selection algorithm dramatically increases the success rate of service requests and avoids overloading nodes.