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首页> 外文期刊>IEEE Journal on Selected Areas in Communications >Non-Cooperative Multicast and Facility Location Games
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Non-Cooperative Multicast and Facility Location Games

机译:非合作式多播和设施定位游戏

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We consider a multicast game with selfish non- cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium. The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with in players, we establish an upper bound of O(radicnlog2 n) on the price of anarchy, and a lower bound of Omega(log n/log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.
机译:我们考虑具有自私的非合作玩家的多播游戏。有一个特殊的源节点,每个玩家都希望通过做出将其支付减至最少的路由决策来连接到源。参与者之间的相互影响由成本分担机制决定,在我们的案例中,这种机制将使用边缘的参与者的成本平均分配。我们考虑两种不同的模型:一个整体模型(其中每个参与者通过选择一条路径连接到源),以及一个分数模型(其中一个参与者被允许在多个路径之间分配从源接收的流)。在这两个模型中,我们都研究了由于用户的自私行为而导致的网络成本开销,以及寻找纳什均衡的计算复杂性。先前已经通过势函数建立了积分模型的纳什均衡。我们证明,找到使势函数最小的Nash平衡是NP-难的。我们关注的是纳什均衡的无政府状态的价格,该价格是由游戏过程的最佳响应动力学产生的,在此过程中,玩家依次加入游戏。对于有in玩家的游戏,我们在无政府状态的价格上确定O(radicnlog2 n)的上限,在Omega上确定下限(log n / log log n)。对于分数模型,我们通过势函数证明了Nash均衡的存在,并给出了多项式时间算法来计算使势函数最小的均衡。最后,我们考虑了多播游戏的加权扩展,并证明了在分数模型中,游戏始终具有纳什均衡。

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