The self-organizing management mode in P2P networks leads to a large amount of selfish behaviors among peers.The corresponding solutions to this problem could hardly keep the merits of P2P network simultaneously

such as self-organization or dynamic scalability.Most of the proposed reputation management models or incentive ones use the flooding mechanism to learn historical behaviour information of other peers

which causes excessive incurred packets

and thus limits the dynamic scalability.A novel incentive framework named as ResP2P based on random matching games theory is given in the paper.Peer reputation and its renewal mechanism

along with some essential social norms are introduced in ResP2P model

which stimulates rational peers to maximize their own utility and contribute their free resource.Experiments have verified the validity and efficiency of the incentive mechanism.The relative distributed algorithm can easily be deployed in a P2P networks and satisfied with self-organization and scalability.