Towards Traffic Benchmarks for Empirical Networking Research: The Role of Connection Structure in Traffic Workload Modeling

Jay Aikat, Shaddi Hasan, K. Jeffay, F. D. Smith
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引用次数: 5

Abstract

Networking research would be well served by the adoption of a set of traffic benchmarks to model network applications for empirical evaluations; such benchmarks are common in many other areas of computing. While it has long been known that certain aspects of modeling traffic, such as round trip time, can dramatically affect application and network performance, there is still no agreement as to how such components should be controlled within an experiment. In this paper we advance the discussion of standards for empirical networking research by demonstrating how certain components of network traffic, such as the structure of application data exchanges within a TCP connection, can have a larger impact on the results obtained through experimentation than other dimensions of traffic such as round-trip time. Such findings point to the pressing need for traffic benchmarks in networking research. Through testbed experiments performed with synthetically generated network traffic from two very different traffic sources, and using several models of TCP connection structure, we demonstrate the strong effects of connection structure in traffic workload modeling on performance measures such as queue length at routers, number of active connections in the network, user response times, and connection durations.
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面向实证网络研究的流量基准:连接结构在流量负荷建模中的作用
采用一套流量基准来模拟网络应用程序以进行实证评估,将很好地服务于网络研究;这样的基准测试在许多其他计算领域都很常见。虽然人们早就知道建模流量的某些方面(如往返时间)会极大地影响应用程序和网络性能,但对于如何在实验中控制这些组件,仍然没有达成一致。在本文中,我们通过展示网络流量的某些组成部分(如TCP连接内应用程序数据交换的结构)如何比流量的其他维度(如往返时间)对通过实验获得的结果产生更大的影响,从而推进了对经验网络研究标准的讨论。这些发现表明,在网络研究中迫切需要流量基准。通过对来自两个非常不同的流量源的综合生成的网络流量进行测试,并使用几种TCP连接结构模型,我们证明了流量工作负载建模中连接结构对性能指标(如路由器队列长度、网络中活动连接数、用户响应时间和连接持续时间)的强烈影响。
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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