Mitigating interference in a network measurement service

S. Gangam, S. Fahmy
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引用次数: 7

Abstract

Shared measurement services offer key advantages over conventional ad-hoc techniques for network monitoring. A measurement service may receive measurement requests concurrently from different applications and network administrators. These measurement requests are often served by injecting active network measurement traffic between two hosts. Two active measurements are said to interfere when the probe packets of one measurement tool are viewed as network traffic by the other. This may lead to faulty measurement readings. In this paper, we model the measurement interference problem, and show how to schedule measurement tasks to reduce interference and hence increase measurement accuracy. We propose twelve computationally tractable algorithms that decrease the total completion time (makespan) of measurement tasks, while avoiding interference. Our evaluation shows that the algorithm we refer to as Largest Area First, Busiest Node First — Earliest Interval Schedule (LAFBNF-EIS) has a mean makespan of about 5% more than the theoretical lower bound over our set of measurement workloads.1
减轻网络测量服务中的干扰
共享测量服务与传统的自组织网络监控技术相比具有关键优势。度量服务可以同时接收来自不同应用程序和网络管理员的度量请求。这些测量请求通常通过在两台主机之间注入活动网络测量流量来满足。当一个测量工具的探测数据包被另一个测量工具视为网络流量时,两个活动测量被称为干扰。这可能导致错误的测量读数。在本文中,我们建立了测量干扰问题的模型,并展示了如何调度测量任务以减少干扰从而提高测量精度。我们提出了12种计算易于处理的算法,减少测量任务的总完成时间(makespan),同时避免干扰。我们的评估表明,我们称之为“最大区域优先,最繁忙节点优先-最早间隔调度”(LAFBNF-EIS)的算法在我们的测量工作负载集上的平均完工时间比理论下界高出约5%
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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