Title: A swarm intelligence learning model of adaptive incentive protocols for P2P networks

Authors: Zheng Wang

Addresses: Qingdao University, 308 Ningxia Road, Qingdao, China

Abstract: Incentive protocols are critical for promoting contribution and cooperation among peers in P2P networks. The behaviour of peers has a significant impact on the effects of incentive protocols. Inspired by the biological systems, a swarm intelligence learning model of adaptive incentive protocols is proposed for P2P networks. The learning model is designed by having peers as particles in the moving swarm. The learning and adaption of peers are guided by the current best strategy as well as the best strategy in history. Simulation results demonstrate that the proposed learning model has a faster convergence rate towards at least the quasi-optimum than the two existing learning models.

Keywords: P2P networks; incentive protocols; learning model; swarm intelligence.

DOI: 10.1504/IJCNDS.2018.089770

International Journal of Communication Networks and Distributed Systems, 2018 Vol.20 No.2, pp.168 - 189

Accepted: 27 Apr 2017
Published online: 09 Feb 2018 *

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