In this paper we develop a simple analytic characterization of the steady state throughput, as a function of loss rate and round trip time for a bulk transfer TCP flow, i.e., a flow with an unlimited amount of data to send. Unlike the models in [6, 7, 10], our model captures not only the behavior of TCP’s fast retransmit mechanism (which is also considered in [6, 7, 10]) but also the effect of TCP’s timeout mechanism on throughput. Our measurements suggest that this latter behavior is important from a modeling perspective, as almost all of our TCP traces contained more timeout events than fast retransmit events. Our measurements demonstrate that our model is able to more accurately predict TCP throughput and is accurate over a wider range of loss rates. This material is based upon work supported by the National Science Foundation under grants NCR-95-08274, NCR-95-23807 and CDA-95-02639. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Abstract-End-to-end congestion control mechanisms have been critical to the robustness and stability of the Internet. Most of today’s Internet trafftc is TCP, and we expect this to remain so in the future. Thus, having “TCP-friendly ” behavior is crucial for new applications. However, the emergence of non-congestion-controlled realtime applications threatens unfairness to competing TCP traffic and possible congestion collapse. We present an end-to-end TCP-friendly Rate Adaptation Protocol (RAP), which employs an additive-increase, multiplicativedecrease (AIMD) algorithm. It is well suited for unicast playback of realtime streams and other semi-reliable rate-based applications. Its primary goal is to be fair and TCP-friendly while separating network congestion control from application-level reliability. We evaluate RAP through extensive simulation, and conclude that bandwidth is usually evenly shared between TCP and RAP traffic. Unfairness to TCP traffic is directly determined by how TCP diverges from the AIMD algorithm. Basic RAP behaves in a TCPfriendly fashion in a wide range of likely conditions, but we also devised a fine-grain rate adaptation mechanism to extend this range further. Finally, we show that deploying RED queue management can result in an ideal fairness between TCP and RAP traffic. I.

Abstract—The steady-state performance of a bulk transfer TCP flow (i.e., a flow with a large amount of data to send, such as FTP transfers) may be characterized by the send rate, which is the amount of data sent by the sender in unit time. In this paper we develop a simple analytic characterization of the steady-state send rate as a function of loss rate and round trip time (RTT) for a bulk transfer TCP flow. Unlike the models in [7]–[9], and [12], our model captures not only the behavior of the fast retransmit mechanism but also the effect of the time-out mechanism. Our measurements suggest that this latter behavior is important from a modeling perspective, as almost all of our TCP traces contained more time-out events than fast retransmit events. Our measurements demonstrate that our model is able to more accurately predict TCP send rate and is accurate over a wider range of loss rates. We also present a simple extension of our model to compute the throughput of a bulk transfer TCP flow, which is defined as the amount of data received by the receiver in unit time. Index Terms—Empirical validation, modeling, retransmission timeouts, TCP.

The path taken by a packet traveling across the Internet depends on a large number of factors, including routing protocols and pernetwork routing policies. The impact of these factors on the endto -end performance experienced by users is poorly understood. In this paper, we conduct a measurement-based study comparing the performance seen using the "default" path taken in the Internet with the potential performance available using some alternate path. Our study uses five distinct datasets containing measurements of "path quality", such as round-trip time, loss rate, and bandwidth, taken between pairs of geographically diverse Internet hosts. We construct the set of potential alternate paths by composing these measurements to form new synthetic paths. We find that in 30-80% of the cases, there is an alternate path with significantly superior quality. We argue that the overall result is robust and we explore two hypotheses for explaining it.

We describe FAST TCP, a new TCP congestion control algorithm for high-speed long-latency networks, from design to implementation. We highlight the approach taken by FAST TCP to address the four difficulties, at both packet and flow levels, which the current TCP implementation has at large windows. We describe the architecture and characterize the equilibrium and stability properties of FAST TCP. We present experimental results comparing our first Linux prototype with TCP Reno, HSTCP, and STCP in terms of throughput, fairness, stability, and responsiveness. FAST TCP aims to rapidly stabilize high-speed long-latency networks into steady, efficient and fair operating points, in dynamic sharing environments, and the preliminary results are promising.

We propose a duality model of congestion control and apply it to understand the equilibrium properties of TCP and active queue management schemes. Congestion control is the interaction of source rates with certain congestion measures at network links. The basic idea is to regard source rates as primal variables and congestion measures as dual variables, and congestion control as a distributed primal-dual algorithm carried out over the Internet to maximize aggregate utility subject to capacity constraints. The primal iteration is carried out by TCP algorithms such as Reno or Vegas, and the dual iteration is carried out by queue management such as DropTail, RED or REM. We present these algorithms and their generalizations, derive their utility functions, and study their interaction.

This paper addresses the problem of streaming packetized media

The more information about current network conditions available to a transport protocol, the more efficiently it can use the network to transfer its data. In networks such as the Internet, the transport protocol must often form its own estimates of network properties based on measurements performed by the connection endpoints. We consider two basic transport estimation problems: determining the setting of the retransmission timer (RTO) for a reliable protocol, and estimating the bandwidth available to a connection as it begins. We look at both of these problems in the context of TCP, using a large TCP measurement set [Pax97b] for trace-driven simulations. For RTO estimation, we evaluate a number of different algorithms, finding that the performance of the estimators is dominated by their minimum values, and to a lesser extent, the timer granularity, while being virtually unaffected by how often round-trip time measurements are made or the settings of the parameters in the exponentially-weighted moving average estimators commonly used. For bandwidth estimation, we explore techniques previously sketched in the literature [Hoe96, AD98] and find that in practice they perform less well than anticipated. We then develop a receiver-side algorithm that performs significantly better. 1

Abstract—Several analytic models describe the steady-state throughput of bulk transfer TCP flows as a function of round trip time and packet loss rate. These models describe flows based on the assumption that they are long enough to sustain many packet losses. However, most TCP transfers across today’s Internet are short enough to see few, if any, losses and consequently their performance is dominated by startup effects such as connection establishment and slow start. This paper extends the steadystate model proposed in [34] in order to capture these startup effects. The extended model characterizes the expected value and distribution of TCP connection establishment and data transfer latency as a function of transfer size, round trip time, and packet loss rate. Using simulations, controlled measurements of TCP transfers, and live Web measurements we show that, unlike earlier steady-state models for TCP performance, our extended model describes connection establishment and data transfer latency under a range of packet loss conditions, including no loss. I.

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