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A fuzzy-based approach to remove clock skew and reset from one-way delay measurement

机译:一种基于模糊的方法,可消除单向延迟测量中的时钟偏斜和复位

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One-way delay (OWD) traces are important measurements for analyzing end-to-end performance on the Internet. It is still a great challenge to provide a scalable solution for large-scale OWD measurement. Because the clocks at end systems are usually not synchronized, the OWD measurements are often inaccurate. For the more challenging case with clock resets to some reference times during the measurement, the OWD measurements are more inaccurate. Furthermore, the measurement data often exhibit considerable network-induced noise when the network is heavily loaded. All the existing OWD measurement techniques, such as linear programming and convex-hull approach (CHA), try to solve this problem by deterministic mathematics model. However, they often fail to distinguish clock resets from temporary Internet congestion. Based on the fuzzy-clustering analysis, this paper proposes a new algorithm to estimate and remove the clock skews and resets from measurement results. This algorithm has been implemented as a tool called fuzzy-based OWD corrector (FOC). The paper then presents OWD measurements of several Internet paths using FOC. Numerical experiments demonstrate that FOC is more accurate and robust than the existing techniques. FOCs computation complexity O(N) is similar to that of CHA and its computing time is much less than that of convex-hull technique.
机译:单向延迟(OWD)跟踪是分析Internet上端到端性能的重要度量。为大规模OWD测量提供可扩展的解决方案仍然是一个巨大的挑战。由于终端系统上的时钟通常不同步,因此OWD测量通常不准确。对于在测量期间将时钟重置为某些参考时间的更具挑战性的情况,OWD测量更加不准确。此外,当网络负载较重时,测量数据通常会表现出相当大的网络感应噪声。所有现有的OWD测量技术,例如线性规划和凸壳方法(CHA),都试图通过确定性数学模型来解决此问题。但是,它们通常无法将时钟重置与暂时的Internet拥塞区分开。在模糊聚类分析的基础上,提出了一种新的算法来估计和消除测量结果中的时钟偏斜和复位。该算法已实现为称为基于模糊的OWD校正器(FOC)的工具。然后,本文介绍了使用FOC进行的几种Internet路径的OWD测量。数值实验表明,FOC比现有技术更准确,更可靠。 FOC的计算复杂度O(N)与CHA相似,其计算时间比凸包技术要少得多。

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