Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval

The need for reputation assessment is particularly strong in peer-to-peer (P2P) systems because the peers' personal site autonomy is amplified by the inherent technological decentralization of the environment. However, the decentralization notion makes the problem of designing a P2P-based reputation assessment substantially harder in P2P networks than in centralized settings. Existing reputation systems tackle the reputation assessment process in an ad hoc manner. There is no systematic and coherent way to derive measures and analyze the current reputation systems. In this paper, we propose a reputation assessment process and use it to classify the existing reputation systems. Simulation experiments are conducted and focused on the different methods in selecting the recommendation sources and collecting the recommendations. These two phases can contribute significantly to the overall performance owing to precision, recall, and communication cost.