A step toward realistic performance evaluation of high-speed TCP variants
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of congestion control al- gorithms from the standard TCP stack (with the exception
of FAST that has an implementation in Linux kernel 2.4 because FAST is not
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A Step toward Realistic Performance Evaluation of High-Speed TCP Variants
Sangtae Ha, Yusung Kim, Long Le, Injong Rhee
Department of Computer Science North Carolina State University Raleigh, NC 27695
Abstract: This is a work-in-progress report on our work on designing realistic evaluation suites for testing high-speed TCP variants. In this work, we have created an experimental network model that captures some of the complex characteristics of propagation delays and background traffic [14, 15, 20]. We use our network model to evaluate a large collection of recently proposed TCPs for high-speed networks: BIC TCP, CUBIC, FAST, HSTCP, H-TCP, and STCP. While we do not claim that we have the most realistic experimental network model, we believe that our work is a right step towards improving experimental methodologies for evaluating network protocols. In this report, we show how protocols could behave differently under the presence or absence of background traffic, and point out the danger of drawing conclusions based on testing under an isolated case of no background traffic.
Lisong Xu
Department of Computer Science and Engineering University of Nebraska Lincoln, NE 68588
tion control algorithms are very sensitive to environmental variables such as background traffic and propagation delays, thorough performance evaluations of TCPs for high-speed networks require creating realistic network environments where these protocols are likely to be used. There are many factors in constructing realistic network testing environments. Most frequently used factors include end-to-end characteristics such as (1) bottleneck bandwidth, (2) round-trip times of protocol flows being observed, (3) the network topology over the path that protocol flows of interest travel through, and (4) queue size at the bottleneck link. These factors are more or less statically captured in a simulation and do not change over the course of the experiment. What is missing in most of existing evaluation work is the considerations of (1) what the protocol flows of interest dynamically (i.e., in a time-varying manner) experience in the middle of the network path, namely the dynamic statistical properties of background traffic over the intermediate links and (2) the impact of background traffic on the statistical properties on a link. These dynamic characteristics include “background” network traffic over both forward and backward directions of these links. These are background traffic because they are not being measured at end points and can still influence the behaviors of the protocol flows being observed at the end points. There are several reasons why background traffic is important in protocol testing. First, network environments without any randomness in packet arrivals and delays are highly susceptible to the phase effect [25], a commonly observed simulation artifact caused by extreme synchronization of the network flows on the end-to-end path. A good mix of background traffic with diverse arrival patterns and delays reduce the likelihood of the phase effect. Second, a high degree of statistical multiplexing is often assumed in protocol design. For instance, the authors of HSTCP and STCP rely on statistical multiplexing for faster convergence (so criticizing these protocols for slow or no convergence under environments without background traffic is unfair). Today’s Internet contains a varying degree of multiplexing and it is very unlikely that a production network does not contain any mix of background traffic. Third, it enables a study on the impact of the protocol flows on the “passing-through” aggregate traffic. This passing-through traffic is not ob-
1 Introduction
Congestion control is an important component of a transport protocol in a packet-switched shared network. The congestion control algorithm of the widely used transport protocol TCP is responsible for detecting and reacting to overloads in the Internet and has been the key to the Internet’s operational success. However, as link capacity grows and new Internet applications with high-bandwidth demand emerge, TCP performance is unsatisfactory, especially on highspeed and long distance networks. The main reason for this is the conservative behavior of TCP in adjusting its congestion window that governs the senders’ transmission rates. A number of solutions have been proposed to remedy the aforementioned problem of TCP by changing the way in which TCP adapts its congestion window: BIC TCP [1], CUBIC [2], FAST [3], HSTCP [4], H-TCP [5], STCP [6], TCP-Westwood [10], LTCP[27] and TCP-Africa [11]. These new protocols promise to improve TCP performance on high-speed networks significantly and are hence usually called TCPs for high-speed networks. While the design of TCPs for high-speed networks has received a considerable amount of interest, far less attention has been paid to thorough evaluations of these protocols. For example, Internet measurement studies showed complex behaviors and characteristics of Internet traffic [14, 15, 20]. Unfortunately, existing evaluation work [8] did not capture these behaviors in their testing environments. Since conges-
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