Peer-to-peer indirect reciprocity via personal currency

Motivating peers to contribute services is critical to the success of peer-to-peer (P2P) systems. Incentive protocols use reciprocity to enforce contributions. Indirect reciprocity schemes are more efficient than direct reciprocity schemes for large-scale P2P systems under high churn rate. In this paper, we propose an indirect reciprocity scheme, called FairTrade, in which peers issue personal currencies to trade services in a P2P system. Personal currency enables indirect reciprocity without relying on any central banks or authorities. It wins extra robustness over global currency as well as much improved trading flexibility and efficiency over direct reciprocity schemes. The acceptance degree of a personal currency depends on the issuer’s service capability and reliance. Peer credit limit is introduced to represent the amount of personal currency that will be accepted by other peers. Every peer as a creditor applies a Bayesian network model to setting peer credit limit for a trading partner peer as a creditee. The Bayesian network model learns the creditee’s capability and reliability and anticipates the associated profits and risks for credit setting. Using simulations on a file-sharing P2P system, we demonstrate that FairTrade achieves 100%100% success rate of download requests without malicious peers, and maintains over 90%90% success rate even with 50%50% malicious nodes. The system warms up quickly and does not assume any altruistic service or other kind of help. On average, the system traffic stabilizes before peers issue their second download requests. All these good performances are achieved with extremely low trading overhead, which takes up less than 1%1% of the total traffic.

► We propose a personal currency based distributed peer-to-peer (P2P) indirect reciprocity scheme (FairTrade).
► We design a Bayesian network model to set the peer credit in dynamic P2P systems to enforce reciprocity.
► We develop a P2P overlay simulator and evaluate the efficiency, overhead, and robustness of FairTrade.