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On Mechanism Design without Payments for Throughput Maximization

机译:论无偿通过吞吐量的机制设计

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It is well-known that the overall efficiency of a distributed system can suffer if the participating entities seek to maximize their individual performance. Consequently, mechanisms have been designed that force the participants to behave more cooperatively. Most of these game-theoretic solutions rely on payments between participants. Unfortunately, such payments are often cumbersome to implement in practice, especially in dynamic networks and where transaction costs are high. In this paper, we investigate the potential of mechanisms which work without payments. We consider the problem of throughput maximization in multi-channel environments and shed light onto the throughput increase that can be achieved with and without payments. We introduce and analyze two different concepts: the worst-case leverage where we assume that players end up in the worst rational strategy profile, and the average-case leverage where player select a random non-dominated strategy. Our theoretical insights are complemented by simulations.
机译:众所周知,如果参与实体寻求最大程度地发挥其个人绩效,则分布式系统的整体效率可能会受到影响。因此,已经设计了迫使参与者更加合作地行为的机制。这些游戏理论中的大多数解决方案都依赖参与者之间的付款。不幸的是,这种支付在实践中通常很麻烦,特别是在动态网络中且交易成本很高的情况下。在本文中,我们研究了无需付款的机制的潜力。我们考虑了多通道环境中吞吐量最大化的问题,并阐明了有偿和无偿都可以实现的吞吐量增长。我们引入并分析了两个不同的概念:最差情况的杠杆(假设玩家最终处于最差的理性策略配置文件中)和平均情况的杠杆(选择玩家)随机的非主导策略。我们的理论见解得到了模拟的补充。

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