Study of Self-adaptive Strategy Based Incentive Mechanism in Structured P2P System
P2P systems provide peers a dynamic and distributed environment to share resource. Only if peers are voluntarily share with each other can system stably exist. However, peers in such systems are selfish and never want to share even with tiny cost. This ca
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Abstract. P2P systems provide peers a dynamic and distributed environment to share resource. Only if peers are voluntarily share with each other can system stably exist. However, peers in such systems are selfish and never want to share even with tiny cost. This can lead to serious free-riding problems. Incentive mechanisms based on evolutionary game aim at designing new strategies to distinguish defective peers from cooperative peers and induce them to cooperate more. Nevertheless, the behavior patterns of peers are versatile. Using only one certain strategy to depict peers’ behaviors is incomplete. In this paper, we propose an adaptive strategy which integrates advantages of 3 classic strategies. These 3 strategies form a knowledge base. Each time a peer with this strategy can select one adjusting to system status according to the adaptive function. Through experiments, we find that in structured system, this strategy can not only promote cooperation but also the system performance. Keywords: Adaptive function
Incentive mechanism Evolutionary game
1 Introduction Autonomous systems, such as P2P system have been widely used due to their openness and anonymity. The stability of such systems severely relies on the selflessness of peers and cooperation among peers. But peers participate in the system are rational. These selfish peers in P2P system tend to deny service request in order to maximize their own profit. Without any incentive, free-riding problem arises and performance of system declined. So promoting cooperation in P2P system becomes significant. To encourage peers to voluntarily share in the system, incentive mechanisms are brought in. The essence of incentive is that through providing transaction history to help peers know the service requester and have a better decision on service granting. In this way, peers with poor history can hardly get service from others. To get better service in the following transactions, peers have to voluntarily make contributions, so that cooperation among peers promoted. Incentive mechanism can be divided into different types: micro-payment based [1], reputation based [2–4], genetic algorithm based [5], global trust based [6], market mechanism based [7], social norm based [8], etc. Normally, peers in P2P system are treated as rational and strategic. They try to maximize their utility by participating the system but never want to cost anything. So evolutionary game [9] is a suitable tool to model the peers and interactions among © Springer International Publishing Switzerland 2016 D.-S. Huang et al. (Eds.): ICIC 2016, Part III, LNAI 9773, pp. 658–670, 2016. DOI: 10.1007/978-3-319-42297-8_61
Study of Self-adaptive Strategy Based Incentive Mechanism
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them. It can reveal the pattern of evolution of the system. So many studies propose new incentive strategies to distinguish cooperative peers and promote cooperation among peers. By far, incentive mechanism based on evolutionary game mainly focus on designing reciprocative strategy. Peers with reciprocative strategy make de
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