From selfish nodes to cooperative networks - emergent link-based incentives in peer-to-peer networks

Abstract

For peer-to-peer (P2P) systems to operate effectively peers need to cooperate for the benefit of the network as a whole. Most existing P2P systems assume cooperation, relying on peers to perform tasks that are of no direct individual benefit. However, when large open systems are deployed such assumptions no longer hold because by adapting selfishly nodes may become freeloaders leaching resources from the network. We present initial results from simulations of an algorithm allowing nodes to adapt selfishly yet maintaining high levels of cooperation in both a Prisoners' dilemma and a flood-fill query scenario. The algorithm does not require centralized or third party reputation systems, the monitoring of neighbor behavior or the explicit programming of incentives and operates in highly dynamic and noisy networks. The algorithm appears to emerge its own incentive structure.