A relative probability based incentive mechanism in P2P systems

Incentive mechanisms in P2P systems have become a hot research field since more and more free-riders are coming out in P2P systems. Many strategies have been proposed and applied, and models are built to analyze these strategies. In this paper, we propose a novel incentive mechanism based on relative probability in a model more like a real implemented system, and compare it to reciprocative strategy, an absolute probability based mechanism. Experiments show that in this model, relative probability based mechanisms are as efficient as other ones, and are more robust to non-cooperators´ cheating.