Evaluation of active measurement tools for bandwidth estimation in real environment

Y. Labit, P. Owezarski, N. Larrieu
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引用次数: 32

Abstract

Available bandwidth - as well as capacity or achievable bandwidth - on a path or a link is one of the very important parameters to measure or estimate in a network: it is of high interest for many networking functions (routing, admission and congestion control, load balancing, etc). Active probing techniques provide the easiest and the more flexible approach, for estimating available bandwidth. In addition, they can be used for different network technologies or structures. Many techniques and tools for available bandwidth estimation appeared recently, but little attention has been given to the accuracy of the estimated values in the real Internet, most of previous studies focusing on validating the accuracy of these tools on local platform. Therefore, this paper deals with evaluating the accuracy of active estimation tools in the real wide area Internet. We use passive monitoring tools for this purpose. We then built a platform combining active and passive equipments, and define a methodology for evaluating active probing techniques using passive tools. The passive evaluation relies on DAG system cards that represent references for such kind of measurements. This paper then discusses the results we got in the different experiments with different tools. In particular, we use traffic generators for changing the characteristics of the traffic on the Internet paths, which we are making our measurements on. It is useful for analyzing the accuracy of active estimation tools according to network and traffic conditions.
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实际环境中用于带宽估计的主动测量工具的评价
路径或链路上的可用带宽——以及容量或可实现带宽——是网络中测量或估计的非常重要的参数之一:它对许多网络功能(路由、接纳和拥塞控制、负载平衡等)都非常重要。主动探测技术为估计可用带宽提供了最简单和更灵活的方法。此外,它们还可以用于不同的网络技术或结构。近年来出现了许多可用带宽估计的技术和工具,但很少关注实际互联网中估计值的准确性,以往的研究大多侧重于在本地平台上验证这些工具的准确性。因此,本文讨论了在实际广域互联网中评估主动估计工具的准确性。为此,我们使用被动监控工具。然后,我们建立了一个结合主动和被动设备的平台,并定义了一种使用被动工具评估主动探测技术的方法。被动评估依赖于DAG系统卡片,这些卡片代表了此类测量的参考。然后讨论了用不同工具进行不同实验得到的结果。特别是,我们使用流量生成器来改变互联网路径上的流量特征,我们正在对其进行测量。这有助于根据网络和交通状况分析主动估计工具的准确性。
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