估计Chord网络大小的抽样算法的评价

Gabriele Falace, Paolo Trunfio
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引用次数: 0

摘要

由于结构化P2P系统的分散性,单个节点无法直接获得整个网络的汇总统计信息,例如其当前规模。在本文中,我们重点研究了使用基于抽样的方法估计最流行的结构化P2P网络之一Chord的大小问题。使用这种方法,节点在查询少量后续节点的一些属性后,计算网络大小的估计。我们正式定义了三种基于采样的算法,它们利用Chord网络的众所周知的结构特性来得出其大小的估计。通过仿真对三种算法在不同网络场景下的准确性进行了实验评估。评估使我们能够在三种算法中识别出一种环密度估计(RDE)技术,该技术能够估计所有Chord网络的大小,平均误差为2%或更小,仅使用几十个样本节点。此外,仿真结果表明,即使在高节点故障率的情况下,RDE精度也不受动态网络条件的影响。
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An evaluation of sampling algorithms for estimating the size of a Chord network
Due to the decentralized nature of structured P2P systems, there is no a direct way for a single node of getting aggregate statistics about the whole network, such as its current size. In this paper we focus on the problem of estimating the size of one of the most popular structured P2P networks, Chord, using a sampling-based approach. With this approach, a node calculates an estimate of the network size after having queried a small number of its successors about some of their properties. We formally define three sampling-based algorithms that exploit well-known structural properties of a Chord network to derive an estimate of its size. An experimental evaluation was carried out through simulations to evaluate the accuracy of the three algorithms in different network scenarios. The evaluation allowed us to identify, among the three algorithms, a Ring Density Estimation (RDE) technique that was able to estimate the size of all the Chord networks considered with an average error of 2% or less, using only a few tens of sample nodes. Moreover, the simulation results showed that the RDE accuracy is not affected by dynamic network conditions, even in the presence of high nodes failure rates.
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