Emergent Mind

Peer-to-Peer Multimedia Sharing based on Social Norms

(1102.1503)
Published Feb 8, 2011 in cs.MM and cs.SI

Abstract

Empirical data shows that in the absence of incentives, a peer participating in a Peer-to-Peer (P2P) network wishes to free-riding. Most solutions for providing incentives in P2P networks are based on direct reciprocity, which are not appropriate for most P2P multimedia sharing networks due to the unique features exhibited by such networks: large populations of anonymous agents interacting infrequently, asymmetric interests of peers, network errors, and multiple concurrent transactions. In this paper, we design and rigorously analyze a new family of incentive protocols that utilizes indirect reciprocity which is based on the design of efficient social norms. In the proposed P2P protocols, the social norms consist of a social strategy, which represents the rule prescribing to the peers when they should or should not provide content to other peers, and a reputation scheme, which rewards or punishes peers depending on whether they comply or not with the social strategy. We first define the concept of a sustainable social norm, under which no peer has an incentive to deviate. We then formulate the problem of designing optimal social norms, which selects the social norm that maximizes the network performance among all sustainable social norms. Hence, we prove that it becomes in the self-interest of peers to contribute their content to the network rather than to free-ride. We also investigate the impact of various punishment schemes on the social welfare as well as how should the optimal social norms be designed if altruistic and malicious peers are active in the network. Our results show that optimal social norms are capable of providing significant improvements in the sharing efficiency of multimedia P2P networks.

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