Lack of cooperation (free riding) is one of the key problems that
confronts today’s P2P systems. What makes this problem partic-
ularly difficult is the unique set of challenges that P2P systems
pose: large populations, high turnover, asymmetry of interest, collu-
sion, zero-cost identities, and traitors. To tackle these challenges we
model the P2P system using the Generalized Prisoner’s Dilemma
(GPD), and propose the Reciprocative decision function as the ba-
sis of a family of incentives techniques. These techniques are fully
distributed 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.
p2pecon.berkeley.edu
