Incentivizing connectivity in structured Peer-to-Peer systems

Peer-to-Peer systems (P2P systems) have received much attention both in research and in practice. P2P systems consist of autonomous entities, as peers are software artifacts chosen and controlled by humans, or they may be humans themselves, as in social networks. Thus, a peer can choose (a) its action-selection strategy, i.e., how it deals with queries on behalf of others, and (b) its link-selection strategy. In so-called structured P2P systems, a peer typically does not interact directly with another one on the application level, but forwards its queries via intermediate peers. Peers in P2P systems expect some benefit from participating. In particular, they benefit if the system is efficient, i.e., if the payoff of all participants is maximal. Since maintaining contacts incurs costs, having only few contacts is attractive. Consequently, we expect some peers to be deliberately poorly connected (dpc): They hardly have any contacts and hence low maintenance costs. Still, a dpc peer benefits from the network structure, since other peers forward its queries via their contacts. In other words, dpc is a new kind of free riding behavior, namely on the contact level (as opposed to free riding on the action level). Since, from a global perspective, a lower degree of connectivity and a higher forwarding load than necessary result, dpc reduces efficiency. In this article we introduce a formal model to show that in many situations dpc indeed leads to a higher payoff than having many links, i.e., cooperation. Further, we show by means of an economic experiment that humans actually do resort to dpc in network-formation situations. To deal with this situation, we propose an incentive mechanism against dpc. The idea is that participants are more cooperative against peers which obviously are not dpc, compared to other peers. We show the effectiveness of our mechanism with a formal analysis.

[1]  J. Quiggin Generalized expected utility theory , 1992 .

[2]  W. Hamilton,et al.  The evolution of cooperation. , 1984, Science.

[3]  Sanjeev Goyal,et al.  Learning, Network Formation and Coordination , 2000 .

[4]  Jiming Liu,et al.  From Local Behaviors to the Dynamics in an Agent Network , 2006, 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06).

[5]  Sanjeev Goyal,et al.  A strategic analysis of network reliability , 2000 .

[6]  David R. Karger,et al.  Chord: A scalable peer-to-peer lookup service for internet applications , 2001, SIGCOMM '01.

[7]  R. Jurca,et al.  "CONFESS" an incentive compatible reputation mechanism for the hotel booking industry , 2004, Proceedings. IEEE International Conference on e-Commerce Technology, 2004. CEC 2004..

[8]  Fernando Vega-Redondo,et al.  Migration and the Evolution of Conventions , 2004 .

[9]  Ion Stoica,et al.  Robust incentive techniques for peer-to-peer networks , 2004, EC '04.

[10]  Bodo Vogt,et al.  Network formation and coordination games , 2003 .

[11]  J. Quiggin Generalized expected utility theory : the rank-dependent model , 1994 .

[12]  S. Chandrasekhar Stochastic problems in Physics and Astronomy , 1943 .

[13]  Mark Handley,et al.  A scalable content-addressable network , 2001, SIGCOMM '01.

[14]  Larry Carter,et al.  Universal classes of hash functions (Extended Abstract) , 1977, STOC '77.

[15]  M. Jackson,et al.  A Strategic Model of Social and Economic Networks , 1996 .

[16]  Jon Crowcroft,et al.  A survey and comparison of peer-to-peer overlay network schemes , 2005, IEEE Communications Surveys & Tutorials.

[17]  Nicolas Christin,et al.  A cost-based analysis of overlay routing geometries , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[18]  Jon M. Kleinberg,et al.  The small-world phenomenon: an algorithmic perspective , 2000, STOC '00.

[19]  Klemens Böhm,et al.  Indirect partner interaction in peer-to-peer networks: stimulating cooperation by means of structure , 2007, EC '07.

[20]  Ion Stoica,et al.  Characterizing selfishly constructed overlay routing networks , 2004, IEEE INFOCOM 2004.

[21]  Boi Faltings,et al.  CONFESS -- An Incentive Compatible Reputation Mechanism for the Online Hotel Booking Industry , 2004, CEC.

[22]  Klemens Böhm,et al.  Incentives engineering for structured P2P systems - a feasibility demonstration using economic experiments , 2006, EC '06.

[23]  Donald F. Towsley,et al.  Modeling peer-peer file sharing systems , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[24]  Haydée Lugo,et al.  Incentives to Cooperate in Network Formation , 2006 .

[25]  Christos H. Papadimitriou,et al.  Free-riding and whitewashing in peer-to-peer systems , 2004, IEEE Journal on Selected Areas in Communications.

[26]  Klemens Böhm,et al.  The Dangers of Poorly Connected Peers in Structured P2P Networks and a Solution Based on Incentives , 2007, Web Intelligence.

[27]  M. Kuperman,et al.  Social games in a social network. , 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  Paul Resnick,et al.  The influence limiter: provably manipulation-resistant recommender systems , 2007, RecSys '07.

[29]  Klemens Böhm,et al.  FairNet - How to Counter Free Riding in Peer-to-Peer Data Structures , 2004, CoopIS/DOA/ODBASE.

[30]  J. Ely Local Conventions , 2002 .

[31]  Stefan Saroiu,et al.  A Measurement Study of Peer-to-Peer File Sharing Systems , 2001 .

[32]  Jia Wang,et al.  Analyzing peer-to-peer traffic across large networks , 2004, IEEE/ACM Trans. Netw..