Analysis and Evaluation Framework Based on Spatial Evolutionary Game Theory for Incentive Mechanism in Peer-to-Peer Network

In peer-to-peer (P2P) network, incentive mechanism is crucial to encourage cooperation among peers. Hence, how to construct a framework to analyze and evaluate the effectiveness of incentive mechanism is a very significant problem. Considering the peers' interactions are influenced by the network structure in real network, we propose a novel framework based on spatial evolutionary game theory. Different from most of other researches based on classical and evolutionary game theory, square lattice network is adopted as the network structure in this paper, without the assumption that peers are well-mixed in P2P network. The square lattice network structure can be easily extended to other realistic complex networks, such as small-world network and scale-free network. The reciprocative incentive mechanism is analyzed and evaluated under the framework with different service benefit. Through the simulation, the range of the parameter Q (cost/benefit) that makes the incentive mechanism work effectively under the framework is got, and the reason is analyzed. In addition, the influences of zero-cost identity and strategy mutation of peers on the incentive mechanism are evaluated. The framework is general to analyze and evaluate the effectiveness of other incentive mechanisms.