BarterCast: A practical approach to prevent lazy freeriding in P2P networks

A well-known problem in P2P systems is freeriding, where users do not share content if there is no incentive to do so. In this paper, we distinguish lazy freeriders that are merely reluctant to share but follow the protocol, versus die-hard freeriders that employ sophisticated methods to subvert the protocol. Existing incentive designs often provide theoretically attractive resistance against die-hard freeriding, yet are rarely deployed in real networks because of practical infeasibility. Meanwhile, real communities benefit greatly from prevention of lazy freeriding, but have only centralized technology available to do so. We present a lightweight, fully distributed mechanism called BARTERCAST that prevents lazy freeriding and is deployed in practice. BarterCast uses a maxflow reputation algorithm based on a peer´s private history of its data exchanges as well as indirect information received from other peers. We assess different reputation policies under realistic, trace-based community conditions and show that our mechanism is consistent and effective, even when significant fractions of peers spread false information. Furthermore, we present results of the deployment of BarterCast in the BitTorrent-based Tribler network which currently has thousands of users worldwide.