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Robust incentives via multi‐level Tit‐for‐Tat
Author(s) -
Lian Qiao,
Peng Yu,
Yang Mao,
Zhang Zheng,
Dai Yafei,
Li Xiaoming
Publication year - 2008
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1190
Subject(s) - incentive , computer science , peer to peer , work (physics) , computer security , distributed computing , microeconomics , engineering , economics , mechanical engineering
Much work has been done to address the need for incentive models in real deployed peer‐to‐peer networks. In this paper, we discuss problems found with the incentive model in a large, deployed peer‐to‐peer network, Maze. We evaluate several alternatives, and propose an incentive system that generates preferences for well‐behaved nodes while correctly punishing colluders. We discuss our proposal as a hybrid between Tit‐for‐Tat and EigenTrust, and show its effectiveness through simulation of real traces of the Maze system. Copyright © 2007 John Wiley & Sons, Ltd.