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An Incentive Scheme for Optimizing the Performance of Data-Driven P2P Streaming System

机译:一种优化数据驱动P2P流系统性能的激励方案

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In the recent years, Internet has witnessed a rapid growth in the deployment of data-driven based peer-to-peer streaming systems. The power of such system arises from the altruism of participating nodes in the system. However, as the system grows larger, the assumption of altruism breaks down since the system may include selfish nodes, which consume the resources provided by other nodes, without contributing any resource to the system. Therefore, the behaviors of selfish nodes will lead to the unfair society as well as the degradation in overall performance of the system. The aim of this paper is to encourage the service providing of nodes in the data-driven P2P streaming system. We first introduce a market model into P2P streaming. In the market, service providers price their services and allocate their bandwidth resource to its consumers, in order to maximize their revenues. Service consumers have the freedom to choose the favorite providers and have to pay for the services they consume. We prove that the optimal system performance can be achieved if each service provider adopts the proper strategy for service pricing and bandwidth allocation. Based on the analysis of market model, we then propose a distributed incentive scheme to encourage the cooperative behaviors of nodes and optimize the system performance concurrently. The results of simulation demonstrate the effectiveness of the proposed incentive scheme.
机译:近年来,互联网目睹了基于数据驱动的对等流系统的部署的快速增长。这种系统的力量出现在系统中参与节点的利他主义。然而,由于系统增长较大,由于系统可以包括自私节点的自私节点,所以利他主义的假设会破坏,这消耗了其他节点提供的资源,而不会将任何资源贡献到系统。因此,自私节点的行为将导致不公平的社会以及系统整体性能的退化。本文的目的是鼓励在数据驱动的P2P流系统中提供节点的服务。我们首先将市场模型介绍为P2P流。在市场上,服务提供商为其服务提供服务,并将其带宽资源分配给其消费者,以最大限度地提高其收入。服务消费者有自由选择最喜欢的提供商,并且必须支付他们消费的服务。如果每个服务提供商采用适当的服务定价策略和带宽分配,我们证明可以实现最佳系统性能。基于市场模式的分析,我们提出了一种分布式激励方案,鼓励节点的合作行为,并同时优化系统性能。仿真结果证明了拟议的激励计划的有效性。

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