首页> 外文会议>Annual European Symposium on Algorithms(ESA 2007); 20071008-10; Eilat(IL) >Tradeoffs and Average-Case Equilibria in Selfish Routing
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Tradeoffs and Average-Case Equilibria in Selfish Routing

机译:自私路由中的权衡和平均情况均衡

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We consider the price of selfish routing in terms of tradeoffs and from an average-case perspective. Each player in a network game seeks to send a message with a certain length by choosing one of several parallel links that have transmission speeds. A player desires to minimize his own transmission time (latency). We study the quality of Nash equilibria of the game, in which no player can decrease his latency by unilaterally changing his link. We treat two important aspects of network-traffic management: the influence of the total traffic upon network performance and fluctuations in the lengths of the messages. We introduce a probabilistic model where message lengths are random variables and evaluate the expected price of anarchy of the game for various social cost functions. For total latency social cost, which was only scarcely considered in previous work so far, we show that the price of anarchy is Θ (n/t), where n is the number of players and t the total message-length. The bound states that the relative quality of Nash equilibria in comparison with the social optimum increase with increasing traffic. This result also transfers to the situation when fluctuations are present, as the expected price of anarchy is O(n/(E[T])), where E [T] is the expected traffic. For maximum latency the expected price of anarchy is even 1 + o(1) for sufficiently large traffic. Our results also have algorithmic implications: Our analyses of the expected prices can be seen average-case analyses of a local search algorithm that computes Nash equilibria in polynomial time.
机译:我们从权衡和平均情况的角度考虑自私路由的价格。网络游戏中的每个玩家都试图通过选择具有传输速度的几个并行链接之一来发送具有一定长度的消息。玩家希望最小化自己的传输时间(延迟)。我们研究了游戏的纳什均衡质量,在这种质量下,没有玩家可以通过单方面改变链接来减少等待时间。我们处理网络流量管理的两个重要方面:总流量对网络性能的影响以及消息长度的波动。我们引入了一种概率模型,其中消息长度是随机变量,并针对各种社会成本函数评估游戏的无政府状态的预期价格。对于总等待时间的社会成本,到目前为止,在以前的工作中几乎没有考虑过,我们证明了无政府状态的价格为Θ(n / t),其中n是玩家人数,t是消息总长度。界限指出,纳什均衡的相对质量与社会最优值相比,随着流量的增加而增加。由于无政府状态的预期价格为O(n /(E [T])),其中E [T]为预期流量,因此该结果也转移到存在波动的情况下。对于最大的延迟,对于足够大的流量,无政府状态的预期价格甚至为1 + o(1)。我们的结果也对算法产生了影响:我们对预期价格的分析可以看作是本地搜索算法的平均情况分析,该算法在多项式时间内计算Nash均衡。

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