Research On Incentive Mechanism Based On Game Theory In P2P Network

As lacking of effective incentives, there exist some ubiquitous problems such as free-riding and'the tragedy of the commons'phenomenon in the traditional P2P (Peer-to-Peer) network which seriously affect the network's robustness and availability. Therefore, how to design and construct efficient incentive mechanism has became one of the hotspot issues of P2P studies. The game theory has been proved to be effectively restrained the free-riding phenomenon in the file sharing system. However, the incentives based on game theory can lead to whitewashing problem. Also in P2P streaming media system, the current incentive mechanism is insufficient in satisfying the requirement for resources, and the node's contribution is neglected. As a consequence, there will be some problems such as unfair scheduling of resources etc. Thus, it has a great academic significance and application value that doing research on the incentive mechanism in P2P networks.Based on the above issues, this thesis analysis the incentive mechanism in P2P network using game theory of economics as guide, and studies of file sharing system and streaming media system as background. On one hand, the equilibrium selection game model of the complete information game is introduced to solve the whitewashing problem. The advantage of this model is that it does not dependent on unified action signals, which makes its process more efficient for simulating the random request of the network node. Moreover, this system has more than one strategies, which the maxmin strategy compensates the deficiency of the traditional incentive system by resolving the new joined node's download request while keeping the system's equilibrium. Simulation experiments shows that this incentive mechanism is not only able to promote the fair distribution of the system resources, it is also increased the contribution of the nodes by restrain the selfish nodes and ensures the system utility.On the other hand, according to the real-time request of playback time and the sequential transmission of media file, this thesis studies on the incentive mechanism in streaming media system with incomplete information game as guide. Especially, the first-price sealed big auction is introduced to modeling the incentive mechanism which makes the resources distribution according to the level of the node's contribution and the urgency of the resource request. Finally, we has improved and optimized the CoolStreaming system, and added the incentive module. The result of the experiment indicates that the proposed incentive mechanism is able to enhance the scheduling efficiency, and ensure the QoS of the nodes.