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Stability-Optimal Grouping Strategy of Peer-to-Peer Systems

机译：对等系统的稳定性最佳分组策略

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When applied in high-churn Internet environments, P2P systems face a dilemma: although most participants are too unstable, a P2P system requires sufficient stable peers to provide satisfactory core services. Thus, determining how to leverage unstable nodes seems to be the only choice. Our primary idea is to group unstable nodes together in order to form an adequate number of stable service groups. Focusing on this topic, our main findings are three-fold: 1) A general analytical model to investigate the grouping process of P2P systems is established, in which the stability-scalability trade-off problem is paid special attention to. 2) We formalize the target of grouping as the Maximum Stability Grouping (MSG) problem. It proves to be not only NP-hard, but also infeasible; therefore, we restrict it to a feasible Homogeneous MSG (H-MSG) problem and deduce its optimal solution under the stochastic model. 3) We propose a homogeneous grouping strategy to fulfill the optimal solution. Comprehensive simulations have been performed on generated data sets and real-world traces from a P2P storage system and a P2P streaming system. Results show that our grouping strategy effectively captures the stability-scalability trade-off: besides excellent stability, it gains much higher stable service capacity, with acceptable loss in scalability.
机译：当在高流量的Internet环境中应用时，P2P系统面临一个难题：尽管大多数参与者都太不稳定了，但是P2P系统需要足够稳定的对等方来提供令人满意的核心服务。因此，确定如何利用不稳定节点似乎是唯一的选择。我们的主要思想是将不稳定的节点分组在一起，以形成足够数量的稳定服务组。针对该主题，我们的主要发现有以下三个方面：1）建立了一个研究P2P系统分组过程的通用分析模型，其中特别关注稳定性-可伸缩性的权衡问题。 2）我们将分组的目标确定为最大稳定性分组（MSG）问题。事实证明，这不仅对NP不利，而且不可行。因此，我们将其限制在可行的均质味精（H-MSG）问题上，并推导其在随机模型下的最优解。 3）我们提出了一种均匀的分组策略来实现最佳解决方案。已经对来自P2P存储系统和P2P流传输系统的生成的数据集和实际跟踪进行了全面的模拟。结果表明，我们的分组策略有效地捕获了稳定性与可伸缩性之间的权衡：除了出色的稳定性外，它还获得了更高的稳定服务容量，而可伸缩性损失却可以接受。

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