CapProbe: a simple and accurate capacity estimation technique for wired and wireless environments

R. Kapoor, Ling-Jyh Chen, A. Nandan, M. Gerla, M. Sanadidi
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引用次数: 70

Abstract

The problem of estimating the capacity of an Internet path is one of fundamental importance. Due to the multitude of potential applications, a large number of solutions have been proposed and evaluated. The proposed solutions so far have been successful in partially addressing the problem, but have suffered from being slow, obtrusive or inaccurate. In this work, we evaluate CapProbe, a low-cost and accurate end-to-end capacity estimation scheme that relies on packet dispersion techniques as well as end-to-end delays. The key observation that enabled the development of CapProbe is that both compression and expansion of packet pair dispersion are the result of queuing due to cross-traffic. By filtering out queuing effects from packet pair samples, CapProbe is able to estimate capacity accurately in most environments, with minimal processing and probing traffic overhead. In fact, the storage and processing requirements of CapProbe are orders of magnitude smaller than most of the previously proposed schemes. We tested CapProbe through simulation, Internet, Internet2 and wireless experiments. We found that CapProbe error percentage in capacity estimation was within 10% in almost all cases, and within 5% in most cases.
CapProbe:一种简单而准确的有线和无线环境容量估计技术
估计互联网路径的容量是一个非常重要的问题。由于潜在的应用众多,已经提出和评估了大量的解决方案。迄今提出的解决办法在部分解决问题方面取得了成功,但速度缓慢、突兀或不准确。在这项工作中,我们评估了CapProbe,这是一种低成本和准确的端到端容量估计方案,它依赖于分组分散技术和端到端延迟。CapProbe开发的关键观察结果是,分组对分散的压缩和扩展都是由于交叉流量导致排队的结果。通过从包对样本中过滤掉排队效应,CapProbe能够在大多数环境中准确地估计容量,而处理和探测流量开销最小。事实上,CapProbe的存储和处理要求比之前提出的大多数方案要小几个数量级。我们通过仿真、Internet、Internet2和无线实验对CapProbe进行了测试。我们发现CapProbe在容量估计中的错误率在几乎所有情况下都在10%以内,在大多数情况下在5%以内。
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