Incentivizing connectivity in structured Peer-to-Peer systems

Björn-Oliver Hartmann, Klemens Böhm, Andranik Khachatryan, Stephan Schosser, B. Vogt
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Abstract

Peer-to-Peer systems (P2P systems) have received much attention both in research and in practice. P2P systems consist of autonomous entities, as peers are software artifacts chosen and controlled by humans, or they may be humans themselves, as in social networks. Thus, a peer can choose (a) its action-selection strategy, i.e., how it deals with queries on behalf of others, and (b) its link-selection strategy. In so-called structured P2P systems, a peer typically does not interact directly with another one on the application level, but forwards its queries via intermediate peers. Peers in P2P systems expect some benefit from participating. In particular, they benefit if the system is efficient, i.e., if the payoff of all participants is maximal. Since maintaining contacts incurs costs, having only few contacts is attractive. Consequently, we expect some peers to be deliberately poorly connected (dpc): They hardly have any contacts and hence low maintenance costs. Still, a dpc peer benefits from the network structure, since other peers forward its queries via their contacts. In other words, dpc is a new kind of free riding behavior, namely on the contact level (as opposed to free riding on the action level). Since, from a global perspective, a lower degree of connectivity and a higher forwarding load than necessary result, dpc reduces efficiency. In this article we introduce a formal model to show that in many situations dpc indeed leads to a higher payoff than having many links, i.e., cooperation. Further, we show by means of an economic experiment that humans actually do resort to dpc in network-formation situations. To deal with this situation, we propose an incentive mechanism against dpc. The idea is that participants are more cooperative against peers which obviously are not dpc, compared to other peers. We show the effectiveness of our mechanism with a formal analysis.
激励结构化点对点系统中的连接
点对点系统(P2P系统)在研究和实践中都受到了广泛的关注。P2P系统由自治实体组成,因为对等体是由人类选择和控制的软件工件,或者它们可能是人类自己,就像在社交网络中一样。因此,一个对等体可以选择(a)它的动作选择策略,即它如何处理代表他人的查询,以及(b)它的链路选择策略。在所谓的结构化P2P系统中,一个对等点通常不直接与应用程序级别的另一个对等点交互,而是通过中间对等点转发其查询。P2P系统中的对等者期望从参与中获得一些好处。特别是,如果系统是有效的,也就是说,如果所有参与者的收益是最大的,他们就会受益。因为维持联系需要成本,所以保持少量的联系是有吸引力的。因此,我们期望一些对等点故意连接不良(dpc):它们几乎没有任何接触,因此维护成本较低。尽管如此,dpc对等体从网络结构中受益,因为其他对等体通过它们的联系人转发它的查询。换句话说,dpc是一种新的搭便车行为,即在接触层面上(而不是在行动层面上)。因为,从全局的角度来看,较低的连接程度和较高的转发负载比必要的结果,dpc降低了效率。在这篇文章中,我们引入了一个正式的模型来证明在许多情况下,dpc确实比拥有许多环节(即合作)带来更高的回报。此外,我们通过一个经济实验表明,在网络形成的情况下,人类实际上会诉诸dpc。针对这种情况,我们提出了一种针对dpc的激励机制。这个想法是参与者在面对同伴时更愿意合作而这些同伴显然不是dpc的。我们用形式化分析来证明我们的机制的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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