This paper proposes a mechanism for equation-based congestion control for unicast traffic. Most best-effort traffic in the current Internet is well-served by the dominant transport protocol, TCP. However, traffic such as best-effort unicast streaming multimedia could find use for a TCP-friendly congestion control mechanism that refrains from reducing the sending rate in half in response to a single packet drop. With our mechanism, the sender explicitly adjusts its sending rate as a function of the measured rate of loss events, where a loss event consists of one or more packets dropped within a single round-trip time. We use both simulations and experiments over the Internet to explore performance. We consider equation-based congestion control a promising avenue of development for congestion control of multicast traffic, and so an additional motivation for this work is to lay a sound basis for the further development of multicast congestion control.

This paper presents a novel framework for managing network congestion from an end-to-end perspective. Our work is motivated by several trends in traffic patterns that threaten the long-term stability of the Internet. These trends include the use of multiple independent concurrent flows by Web applications and the increasing use of transport protocols and applications that do not adapt to congestion. We present an end-system architecture centered around a Congestion Manager (CM) that ensures proper congestion behavior and allows applications to easily adapt to network congestion. Our framework integrates congestion management across all applications and transport protocols. The CM maintains congestion parameters and exposes an API to enable applications to learn about network characteristics, pass information to the CM, and schedule data transmissions. Internally, it uses a stable rate-based control algorithm, a scheduler to regulate transmissions, and a lightweight loss-resilient protocol to elicit feedback from receivers. Its ratebased scheme uses additive increase/multiplicative decrease, combined with a novel exponential aging scheme when receiver feedback is infrequent, to obtain both stable network behavior and good application performance.

This paper introduces and analyzes a class of nonlinear congestion control algorithms called binomial algorithms, motivated in part by the needs of streaming audio and video applications for which a drastic reduction in transmission rate upon each congestion indication (or loss) is problematic. Binomial algorithms generalize TCP-style additive-increase by increasing inversely proportional to a power of the current window (for TCP, ) ; they generalize TCP-style multiplicative-decrease by decreasing proportional to a power of the current window (for TCP, ). We show that there are an infinite number of deployable TCP-compatible binomial algorithms, those which satisfy , and that all binomial algorithms converge to fairness under a synchronized-feedback assumption provided . Our simulation results show that binomial algorithms interact well with TCP across a RED gateway. We focus on two particular algorithms, IIAD ( ) and SQRT ( !" ), showing that they are well-suited to applications that do not react well to large TCP-style window reductions. Keywords--- Congestion control, TCP-friendliness, TCP-compatibility, nonlinear algorithms, transport protocols, TCP, streaming media, Internet. I.

In this paper, we explore the operation of TCP congestion control when the receiver can misbehave, as might occur with a greedy Web client. We first demonstrate that there are simple attacks that allow a misbehaving receiver to drive a standard TCP sender arbitrarily fast, without losing end-to-end reliability. These attacks are widely applicable because they stem from the sender behavior specified in RFC 2581 rather than implementation bugs. We then show that it is possible to modify TCP to eliminate this undesirable behavior entirely, without requiring assumptions of any kind about receiver behavior. This is a strong result: with our solution a receiver can only reduce the data transfer rate by misbehaving, thereby eliminating the incentive to do so. 1

Streaming audio and video applications are becoming increasingly popular on the Internet, and the lack of effective congestion control in such applications is now a cause for significant concern. The problem is one of adapting the compression without requiring video-servers to re-encode the data, and fitting the resulting stream into the rapidly varying available bandwidth. At the same time, rapid fluctuations in quality will be disturbing to the users and so should be avoided. In this paper we present a mechanism for using layered video in the context of unicast congestion control. This quality adaptation mechanism adds and drops layers of the video stream to perform long-term coarse-grain adaptation, while using a TCP-friendly congestion control mechanism to react to congestion on very short timescales. The mismatches between the two timescales are absorbed using buffering at the receiver. We present a piecewiseoptimal scheme for the distribution of buffering among the active layers in order to maximize perceptual quality while minimizing rapid, disturbing changes in the quality. We discuss the issues involved in implementing and tuning such a mechanism, and present our simulation and experimental results.

As networked multimedia applications become widespread, it becomes increasingly important to ensure that these applications can coexist with current TCP-based applications. The TCP protocol is designed to reduce its sending rate when congestion is detected. Networked multimedia applications should exhibit similar behavior, if they wish to co-exist with TCP-based applications [9]. Using TCP for multimedia applications is not practical, since the protocol combines error control and congestion control, an appropriate combination for non-real time reliable data transfer, but inappropriate for loss-tolerant real time applications. In this paper we present a protocol that operates by measuring loss rates and round trip times and then uses them to set the transmission rate to that which TCP would achieve under similar conditions. The analysis in [13] is used to determine this "TCP-friendly" rate. This protocol represents a rst step towards developing a comprehensive protocol for congestion control for time-sensitive multimedia data streams. We evaluate the protocol under various tra c conditions, using simulations and implementation. The simulations are used to study the behavior of the protocol under controlled conditions. The implementation and experimentation involve over 300 experiments over the Internet, using several machines in the US and UK. Our experimental and simulation results show that the protocol is fair to TCP and to other sessions running TFRCP, and that the formula-based approach to achieving TCP-friendliness is indeed practical.

Instead of the increase-by-one decrease-to-half strategy used in TCP Reno for congestion window adjustment, we consider the general case such that the increase value and decrease ratio are parameters. That is, in the congestion avoidance state, the window size is increased by ff per window of packets acknowledged and it is decreased to fi of the current value when there is congestion indication. We refer to this window adjustment strategy as general additive increase multiplicative decrease (GAIMD). We present the (mean) sending rate of a GAIMD flow as a function of ff, fi, loss rate, mean roundtrip time, mean timeout value, and the number of packets acknowledged by each ACK. We conducted extensive experiments to validate this sending rate formula. We found the formula to be quite accurate for a loss rate of up to 20%. We also present in this paper a simple relationship between ff and fi for a GAIMD flow to be TCP-friendly, that is, for the GAIMD flow to have approximately the same sending rate as a TCP flow under the same path conditions.

New trends in communication, in particular the deployment of multicast and real-time audio/video streaming applications, are likely to increase the percentage of non-TCP traffic in the Internet. These applications rarely perform congestion control in a TCP-friendly manner, i.e., they do not share the available bandwidth fairly with applications built on TCP, such as web browsers, FTP- or email-clients. The Internet community strongly fears that the current evolution could lead to a congestion collapse and starvation of TCP traffic. For this reason, TCP-friendly protocols are being developed that behave fairly with respect to co-existent TCP flows. In this article, we present a survey of current approaches to TCP-friendliness and discuss their characteristics. Both unicast and multicast congestion control protocols are examined, and an evaluation of the different approaches is presented.

\Soft state " is an often cited yet vague concept in network protocol design in which two or more network entities intercommunicate in a loosely coupled, often anonymous fashion. Researchers often de ne this concept operationally (if at all) rather than analytically: a source of soft state transmits periodic \refresh messages " over a (lossy) communication channel to one or more receivers that maintain a copy of that state, which in turn \expires " if the periodic updates cease. Though a number of crucial Internet protocol building blocks are rooted in soft state-based designs | e.g., RSVP refresh messages, PIM membership updates, various routing protocol updates, RTCP control messages, directory services like SAP, and so forth | controversy is building as to whether the performance overhead of soft state refresh messages justify their qualitative bene t of enhanced system \robustness". We believe that this controversy has risen not from fundamental performance tradeo s but rather from our lack of a comprehensive understanding of soft state. To better understand these tradeo s, we propose herein a formal model for soft state communication based on a probabilistic delivery model with relaxed reliability. Using this model, we conduct queueing analysis and simulation to characterize the data consistency and performance tradeo s under a range of workloads and network loss rates. We then extend our model with feedback and show, through simulation, that adding feedback dramatically improves data consistency (by up to 55%) without increasing network resource consumption. Our model not only provides a foundation for understanding soft state, but also induces a new fundamental transport protocol based on probabilistic delivery. Toward this end, we sketch our design of the \Soft State Transport Protocol " (SSTP), which enjoys the robustness of soft state while retaining the performance bene t of hard state protocols like TCP through its judicious use of feedback. This research was supported by DARPA contract N66001-96-C-8508, by the State of California under the MICRO program, and by

background transfers transfers of data that humans are not waiting for to improve availability, reliability, latency or consistency. However, given the rapid fluctuations of available network bandwidth and changing resource costs due to technology trends, hand tuning the aggressiveness of background transfers risks (1) complicating applications, (2) being too aggressive and interfering with other applications, and (3) being too timid and not gaining the benefits of background transfers. Our goal is for the operating system to manage network resources in order to provide a simple abstraction of near zero-cost background transfers. Our system, TCP Nice, can provably bound the interference inflicted by background flows on foreground flows in a restricted network model. And our microbenchmarks and case study applications suggest that in practice it interferes little with foreground flows, reaps a large fraction of spare network bandwidth, and simplifies application construction and deployment. For example, in our prefetching case study application, aggressive prefetching improves demand performance by a factor of three when Nice manages resources; but the same prefetching hurts demand performance by a factor of six under standard network congestion control.