摘要
由于资源的有限性,P2P网络节点之间存在大量的竞争,因此了解对方节点的效用是至关重要的,可以根据对方的效用来推测下一时刻它可能采取的行动,以此为参照,采取对自己更有利的行动.基于此,提出了基于博弈论的P2P网络节点效用值的获取算法,在博弈达到均衡的状态下,根据对方的策略,反推他的效用.把求解未知节点的效用看作是一个函数优化问题.定义了目标函数,并把目标函数最优解的求解归结为一组线性规划问题,进而提出了求解目标函数最优解的遗传算法,从而得到节点的效用值.算法的实验研究表明,提出的方法可以求解连续策略空间中P2P系统任意未知节点的效用值,涉及到大规模的网络节点,也有较好的求解精度和求解效率.
For the limited in resources,lots of competition between nodes exists in a P2P network,it is important for a node to get the utility of other nodes. Based on a node' information,it is guessed the possible action it will take in the next time,and to decide taking better action. Based on the above consideration,it is proposed a method of gaining the utility of nodes based on game theory. Under the state of Nash Equilibrium,it is infered the utility of a node according to its action.Solving the unknown utility of a node is considered as a problem of functional optimization. The objective function is defined,and the solving of the optimal solution is boiled down to the problem of a set of linear programming. Then,the genetic algorithm of solving the optimal solution of the objective function is proposed to gain the utility of nodes. Experimental results show that our method is effective,even when the scale of the network nodes is large.
出处
《云南大学学报（自然科学版）》
CAS
CSCD
北大核心
2009年第S1期5-8,共4页
Journal of Yunnan University(Natural Sciences Edition)
基金
国家自然科学基金资助项目(60763007)
云南省应用基础研究资助项目(2008CD083)
云南大学中青年骨干教师培养计划资助
关键词
对等网
博弈论
纳什均衡
遗传算法
Peer-to-Peer (P2P)
game theory
nash equilibrium
genetic algorithm
