一种在点对点网络上有效分发大量内容的资源交易机制

S.G.M. Koo, C.S.G. Lee, Karthik N. Kannan
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引用次数: 10

摘要

近年来,P2P网络的快速发展为内容分发提供了一种新的模式。为了提高P2P系统的效率,重要的是要提供激励机制,使其参与并贡献其资源。通过基于请求节点的历史或声誉提供服务差异化,已经进行了各种各样的尝试来奖励/惩罚节点。然而,在一个真正的分布式、非合作的环境中,维护和防止社区内这些信息的不真实泄露会给系统带来更大的计算和通信开销。当内容量较大时,由于传播过程较长,历史或声誉的更新必须跟上传播过程,这些问题会进一步放大。在本文中,我们解决了P2P网络中大容量内容分发的激励配置问题,并提出了一种“眼见为实”的激励兼容机制(协议),在该机制中,对等体将根据其经历来决定将多少资源分配给哪些邻居。该协议应用了基于效用的资源交易概念,其中节点将最大化他们的贡献以获得公平或更好的回报,并且我们表明通过采用该协议,系统将实现古诺均衡。此外,我们的协议是轻量级的,完全去中心化的,防欺骗的。实验结果表明,与其他已采用的替代方案相比,我们的协议在分配效率上有显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A resource-trading mechanism for efficient distribution of large-volume contents on peer-to-peer networks
In recent years, the rapid growth of peer-to-peer (P2P) networks has provided a new paradigm for content distribution. To improve the efficiency of a P2P system, it is important to provide incentives for the peers to participate and contribute their resources. Various attempts have been made to reward/penalize peers by providing service differentiation based on a requesting peer's history or reputation. However, in a truly distributed, non-cooperative environment, maintaining and preventing the untruthful revealing of such information within the community impose larger computation and communication overheads to the system. These problems are further magnified when large-volume contents are being distributed because of the length distribution processes and the update of history or reputation has to keep up with the distribution process. In this paper, we address the incentive provisioning problem for distribution of large-volume content in P2P networks, and present a "seeing-is-believing" incentive-compatible mechanism (protocol) in which a peer will decide how much resources will be assigned to which neighbors based on what it has experienced. The protocol applies a utility-based resource-trading concept where peers will maximize their contributions for a fair or better return, and we show that by adopting this protocol, the system will achieve Cournot Equilibrium. Furthermore, our protocol is light-weight, completely decentralized, and cheat-proof. Experimental results illustrate significant improvements on the distribution efficiency of our protocol over other adopted alternatives.
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