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Novel incentive based on game theory in P2P networks

XU Hai-mei,ZHENG Xiang-quan,QI Shou-qing,NIE Xiao-wen,

计算机应用研究 , 2008,
Abstract: In order to solve free rider and tragedy of the commons problems in peer-to-peer(P2P) systems,this paper proposed a novel incentive based on game theory.While trying to maximize its own utility subjected to individual rationality,every peer allocated bandwidth resources efficiently according to competing peers' contribution values to maximize the social utility.The simulation result shows that the incentive increased the social utility of the whole P2P system rapidly and incentive every peer to share resources effectively.
Cooperative incentive mechanism based on game theory in mobile P2P networks

NIU Xin-zheng,ZHOU Ming-tian,SHE Kun,

计算机应用 , 2008,
Abstract: Many selfish mobile peers consume much resource without any contribution in mobile P2P network. Considering the limitation of network resource and selfishness of peers, this paper proposed a cooperative incentive mechanism based on game theory. The mechanism provided peers with different network's service quality according to their contribution and therefore every peer was encouraged to cooperate with others or share their resource. This paper described and analyzed the resource allocation policy of cooperative incentive mechanism in detail. Besides, the existence of the steady Nash equilibrium in the game was also proven. Simulation and analysis results show that the incentive mechanism can encourage the cooperation among the peers and improve the network performance efficiently. Compared with current cooperative incentive mechanism, the mechanism can increase forwarding ratio of the packet.
Incentive Mechanisms for Multicast Nodes Based on Second-price Auction Theory in P2P Network

计算机科学 , 2012,
Abstract: The reliability of P2P multicast performance can't be ensured when facing non-cooperation stategies and ma- licious behaviours of P2P nodes. The market model based framework of P2P multicast was proposed, which uses second- price auction for network resource allocation. The stategies and payoff matrixes of various multicast nodes were ana- lyzed,as well as the conditions of stategy adjustment. Then the incentive mechanisms were designed for multicast nodes. Theoretical analysis and simulation results demonstrate its effectiveness.
Debt Relationship Based Fair File Exchange in Distributed Hash Table Network

YU Kun,WU Guo-Xin,XU Li-Bo,CHEN Gang,

软件学报 , 2007,
Abstract: The selfishness of nodes degrades the system usability of P2P network. Debt relationship based file exchange network constructs an incentive mechanism which induces cooperation and guarantees fairness in file exchange. The key point of the mechanism is finite neighbors, an inherent characteristic in DHT (distributed hash table) networks and so is the interacting between nodes form a repeated games. DFFE (debt relationship based fair file exchange in DHT network) protocol only needs to maintain a little local interacting information, so the protocol cost is low and scalable for large network. In routing, one-hop information based greedy arithmetic is used. Game among rational nodes exists a Nash equilibrium and the approximate algorithm of strategy selection gradually converges. Simulations indicate the validity of incentive mechanism and the steady performance in dynamic networks.
A Game Theoretic Analysis of Incentives in Content Production and Sharing over Peer-to-Peer Networks  [PDF]
Jaeok Park,Mihaela van der Schaar
Computer Science , 2009, DOI: 10.1109/JSTSP.2010.2048609
Abstract: User-generated content can be distributed at a low cost using peer-to-peer (P2P) networks, but the free-rider problem hinders the utilization of P2P networks. In order to achieve an efficient use of P2P networks, we investigate fundamental issues on incentives in content production and sharing using game theory. We build a basic model to analyze non-cooperative outcomes without an incentive scheme and then use different game formulations derived from the basic model to examine five incentive schemes: cooperative, payment, repeated interaction, intervention, and enforced full sharing. The results of this paper show that 1) cooperative peers share all produced content while non-cooperative peers do not share at all without an incentive scheme; 2) a cooperative scheme allows peers to consume more content than non-cooperative outcomes do; 3) a cooperative outcome can be achieved among non-cooperative peers by introducing an incentive scheme based on payment, repeated interaction, or intervention; and 4) enforced full sharing has ambiguous welfare effects on peers. In addition to describing the solutions of different formulations, we discuss enforcement and informational requirements to implement each solution, aiming to offer a guideline for protocol designers when designing incentive schemes for P2P networks.
On Incentive Strategies for Trust Recommendations in Wireless Ad Hoc Networks with Probability Game

SUN Yu-xing,ZHAO Yan-fei,LI Y,XIE Li,

计算机科学 , 2011,
Abstract: Trust recommended behaviors rely on the cooperation among nodes in wireless ad hoc network and trust system itself cannot provide trust evaluations for the behaviors. We proposed a repeated probability game to facilitate the study of the interaction process for trust-recommended behaviors between nodes. Based on the model, we analyzed the INFLUENCE of the four types of incentive strategics, namely TFT,GTFT,OT,GT to motivate the trust-recommended behavior between nodes, as well as the DIFFERENCE of the ectuilibrium boundary conditions of the four incentives strategics. Simulation results show that, in the high rate of sudden selfish behaviors, GTFT strategy keeps Efficient Recommendation Ratio at a higher level,motivates the cooperation of trust recommended behaviors and then helps the trust system to make timely and accurate trust evaluations in the case of collusion attacks.
Repeated-Game Modeling of Cooperation Enforcement in Wireless Ad Hoc Network

LU Yin,SHI Jin,XIE Li,

软件学报 , 2008,
Abstract: Due to the absence of centralized authority, the service reliability of wireless ad hoc network is seriously affected by selfish actions of the rational nodes during the packet forwarding. This paper proposes a repeated-game model of node behavior that takes account of the selfish nodes' future payoff expectations and their long-term desires for profit. An incentive-compatible condition under which the selfish one will be deterred from cheating by the subsequent punishments and then turn to cooperate is shown analytically. The impacts on the selfish nodes' behaviors, which are induced by their willingness for future collaboration, the parameter settings of punishment mechanism and the efficiency of misbehavior detection, are also discussed. Simulation results show that, the increase of network scale, the deterioration of node's collaborative patience and the low misbehavior detection efficiency will motivate entities toward self-interested action, but this tendency can be neutralized by a careful configuration of the punishment mechanism in the model.
A Game Theoretic Framework for Incentives in P2P Systems  [PDF]
Chiranjeeb Buragohain,Divyakant Agrawal,Subhash Suri
Computer Science , 2003,
Abstract: Peer-To-Peer (P2P) networks are self-organizing, distributed systems, with no centralized authority or infrastructure. Because of the voluntary participation, the availability of resources in a P2P system can be highly variable and unpredictable. In this paper, we use ideas from Game Theory to study the interaction of strategic and rational peers, and propose a differential service-based incentive scheme to improve the system's performance.
Incentive Mechanism for P2P Networks Based on Markov Chain  [PDF]
Hongwei Chen,Hui Xu,Chunzhi Wang,Ke Zhou
Information Technology Journal , 2011,
Abstract: Due to nodes behavioral analysis, grasping the inertia psychology of its behavior choice and considering whole influences of the network such as group selection, this study establishes the forecast mechanism in P2P network. In the process of network running and node communication, this mechanism carries on real-time surveillance to all nodes, according to the differences of network states and takes the corresponding incentive and penalty measure to the node, thus drives node well serve for the P2P network. This mechanism uses the Markov chain to forecast future development state of the network, combines the forecast of future node state shift situation and adopts more prompt and more effective measure to the network ahead of time. Summarizing the types of network state, each network state mechanism will have a correspond model which will carry on the drive to the node behavior.
On the Effectiveness of Punishments in a Repeated Epidemic Dissemination Game  [PDF]
Xavier Vila?a,Luís Rodrigues
Computer Science , 2013,
Abstract: This work uses Game Theory to study the effectiveness of punishments as an incentive for rational nodes to follow an epidemic dissemination protocol. The dissemination process is modeled as an infinite repetition of a stage game. At the end of each stage, a monitoring mechanism informs each player of the actions of other nodes. The effectiveness of a punishing strategy is measured as the range of values for the benefit-to-cost ratio that sustain cooperation. This paper studies both public and private monitoring. Under public monitoring, we show that direct reciprocity is not an effective incentive, whereas full indirect reciprocity provides a nearly optimal effectiveness. Under private monitoring, we identify necessary conditions regarding the topology of the graph in order for punishments to be effective. When punishments are coordinated, full indirect reciprocity is also effective with private monitoring.
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