Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level
Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level
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DOI：
10.1109/90.554723
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发表时间：
1997-02
期刊：
影响因子：
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通讯作者：
W. Willinger;M. Taqqu;R. Sherman;D. V. Wilson
中科院分区：
文献类型：
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作者：
W. Willinger;M. Taqqu;R. Sherman;D. V. Wilson
许多来自各种工作分组网络的流量测量的经验研究表明，实际网络流量本质上是自相似的或长距离依赖的-这与通常所做的流量建模假设形成鲜明对比。我们为局域网(LAN)流量中自相似现象的发生提供了一个可信的物理解释。我们的解释是基于表现出高度变异性的过程的收敛结果，并得到来自各个源的以太网局域网的实时流量测量的详细统计分析的支持。本文是Willinger等人的扩展版本。(1995年)。我们在这里发展了关于严格交替开/关源叠加的数学结果。我们的关键数学结果表明，许多ON/OFF源(也称为分组串)与严格交替的ON和OFF周期以及其ON周期或OFF周期呈现诺亚效应的叠加产生了呈现约瑟夫效应的聚合网络流量。此外，描述诺亚效应(高变率)和约瑟夫效应(自相似)强度的参数之间有一个简单的关系。对高时间分辨率的以太网局域网流量轨迹的广泛统计分析证实，单个源或源-目的地对级别的数据符合诺亚效应。我们还讨论了这一简单的物理解释对现代高速网络流量中存在自相似流量模式的影响。
A number of empirical studies of traffic measurements from a variety of working packet networks have demonstrated that actual network traffic is self-similar or long-range dependent in nature-in sharp contrast to commonly made traffic modeling assumptions. We provide a plausible physical explanation for the occurrence of self-similarity in local-area network (LAN) traffic. Our explanation is based on convergence results for processes that exhibit high variability and is supported by detailed statistical analyzes of real-time traffic measurements from Ethernet LANs at the level of individual sources. This paper is an extended version of Willinger et al. (1995). We develop here the mathematical results concerning the superposition of strictly alternating ON/OFF sources. Our key mathematical result states that the superposition of many ON/OFF sources (also known as packet-trains) with strictly alternating ON- and OFF-periods and whose ON-periods or OFF-periods exhibit the Noah effect produces aggregate network traffic that exhibits the Joseph effect. There is, moreover, a simple relation between the parameters describing the intensities of the Noah effect (high variability) and the Joseph effect (self-similarity). An extensive statistical analysis of high time-resolution Ethernet LAN traffic traces confirms that the data at the level of individual sources or source-destination pairs are consistent with the Noah effect. We also discuss implications of this simple physical explanation for the presence of self-similar traffic patterns in modern high-speed network traffic.