Robust incentive techniques for peer-to-peer networks. Feldman, M., Lai, K., Stoica, I., & Chuang, J. 05/2004 2004. ![Robust incentive techniques for peer-to-peer networks [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Lack of cooperation (free riding) is one of the key problems that confronts today\textquoterights P2P systems. What makes this problem particularly difficult is the unique set of challenges that P2P systems pose: large populations, high turnover, a symmetry of interest, collusion, zero-cost identities, and traitors. To tackle these challenges we model the P2P system using the Generalized Prisoner\textquoterights Dilemma (GPD),and propose the Reciprocative decision function as the basis of a family of incentives techniques. These techniques are fullydistributed and include: discriminating server selection, maxflow-based subjective reputation, and adaptive stranger policies. Through simulation, we show that these techniques can drive a system of strategic users to nearly optimal levels of cooperation.
@conference {Feldman:2004:RIT:988772.988788,
title = {Robust incentive techniques for peer-to-peer networks},
booktitle = {EC{\textquoteright}04. Proceedings of the 5th ACM Conference on Electronic Commerce},
series = {EC {\textquoteright}04},
year = {2004},
month = {05/2004},
pages = {102{\textendash}111},
publisher = {ACM},
organization = {ACM},
address = {New York, NY, USA},
abstract = {Lack of cooperation (free riding) is one of the key problems that confronts today{\textquoteright}s P2P systems. What makes this problem particularly difficult is the unique set of challenges that P2P systems pose: large populations, high turnover, a symmetry of interest, collusion, zero-cost identities, and traitors. To tackle these challenges we model the P2P system using the Generalized Prisoner{\textquoteright}s Dilemma (GPD),and propose the Reciprocative decision function as the basis of a family of incentives techniques. These techniques are fullydistributed and include: discriminating server selection, maxflow-based subjective reputation, and adaptive stranger policies. Through simulation, we show that these techniques can drive a system of strategic users to nearly optimal levels of cooperation.},
keywords = {cheap pseudonyms, collusion, free-riding, incentives, peer-to-peer networking, prisoners dilemma, reputation, whitewash},
isbn = {1-58113-771-0},
doi = {http://doi.acm.org/10.1145/988772.988788},
url = {http://doi.acm.org/10.1145/988772.988788},
author = {Michal Feldman and Kevin Lai and Ion Stoica and John Chuang}
}
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