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Self-similarity and long range dependence on the internet: a second look at the evidence, origins and implications

机译:自相似性和对互联网的长期依赖性:再看证据,起源和含义

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In this paper we critically reexamine some of the long standing beliefs regarding self-similarity and long range dependence (LRD) on the Internet. Power law tails have been conjectured to be a cause of LRD. In this paper, we reexamine the claims regarding heavy tails. We first examine the generative models for the heavy tail phenomena, both in terms of the fragility of some proposed mechanisms to modeling perturbations as well as the weak statistical evidence for the mechanisms. Next, we take a look at some of the implications of LRD in key performance aspects of Internet algorithms. Finally, we present an alternative model explaining the LRD phenomena of Internet traffic. We argue that the multiple time-scale nature of the generation of traffic and transport protocols make the observation of LRD inevitable.
机译:在本文中,我们批判性地重新审视了一些关于互联网上的自相似性和远程依赖(LRD)的长期存在的信念。据推测,幂法尾巴是造成LRD的原因。在本文中,我们重新检查了有关粗尾的主张。我们首先从一些提议的对扰动建模的机制的脆弱性以及该机制的弱统计证据两方面来研究重尾现象的生成模型。接下来,我们来看一下LRD在Internet算法关键性能方面的一些含义。最后,我们提出了一个替代模型,解释了互联网流量的LRD现象。我们认为,交通和运输协议生成的多重时标性质使得对LRD的观察不可避免。

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