We introduce LT codes, the first rateless erasure codes that are very efficient as the data length grows.

This paper introduces Wave and Equation Based Rate Control (WEBRC), the first multiple rate multicast congestion control protocol to be equation based. The equation-based approach enforces fairness to TCP with the benefit that fluctuations in the flow rate are small in comparison to TCP.

We survey recent advances in theories and models for Internet Quality of Service (QoS). We start with the theory of network calculus, which lays the foundation for support of deterministic performance guarantees in networks, and illustrate its applications to integrated services, differentiated services, and streaming media playback delays. We also present mechanisms and architecture for scalable support of guaranteed services in the Internet, based on the concept of a stateless core. Methods for scalable control operations are also briefly discussed. We then turn our attention to statistical performance guarantees, and describe several new probabilistic results that can be used for a statistical dimensioning of differentiated services. Lastly, we review recent proposals and results in supporting performance guarantees in a best effort context. These include models for elastic throughput guarantees based on TCP performance modeling, techniques for some quality of service differentiation without access control, and methods that allow an application to control the performance it receives, in the absence of network support.

A significant impediment to deployment of multicast services is the daunting technical complexity of developing, testing and validating congestion control protocols fit for wide-area deployment. Protocols such as pgmcc and TFMCC have recently made considerable progress on the single rate case, i.e. where one dynamic reception rate is maintained for all receivers in the session. However, these protocols have limited applicability, since scaling to session sizes beyond tens of participants necessitates the use of multiple rate protocols. Unfortunately, while existing multiple rate protocols exhibit better scalability, they are both less mature than single rate protocols and suffer from high complexity.

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We study limitations of an equation-based congestion control protocol, called TFRC (TCP Friendly Rate Control). It examines how the three main factors that determine TFRC throughput, namely, the TCP friendly equation, loss event rate estimation and delay estimation, can influence the longterm throughput imbalance between TFRC and TCP. Especially, we show that different sending rates of competing flows cause these flows to experience different loss event rates. There are several fundamental reasons why TFRC and TCP flows have different average sending rates, from the first place. Earlier work shows that the convexity of the TCP friendly equation used in TFRC causes the sending rate difference. We report two additional reasons in this paper: (1) the convexity of 1/x where x is a loss event period and (2) different RTO (retransmission timeout period) estimations of TCP and TFRC. These factors can be the reasons for TCP and TFRC to experience initially different sending rates. But we find that the loss event rate difference due to the differing sending rates greatly amplifies the initial throughput difference; in some extreme cases, TFRC uses around 20 times more, or sometimes 10 times less, bandwidth than TCP.

A stochastic model of TCP is developed. Unlike many other models, this model accounts for variations in latency and loss probability. A major strength of this model is that it easily produces the probability distribution of the congestion window. Thus, the mean as well as the median and percentiles can be found. It is shown that the mean congestion window can be far larger than the median. Other new insights include the effect of the rate of change of the latency on the performance of TCP. Specifically, this model predicts the well-known TCP-friendly formula only if the round-trip time rapidly varies. However, if the round-trip time does not vary quickly, then the TCPfriendly formula may not hold. Both rapidly and slowly varying round-trip times have been observed in real networks. As an application of the model, the question as to when a video can be fairly transmitted is addressed. If it is possible to transmit the video, the model yields the distribution of the size of the receiving buffer required to avoid underflow. Since the distribution can be found, it is possible to select a buffer size so that a specified percentage of users will view the video without interruption.

We propose a new TCP-friendly Multicast Congestion Control (MCC) model for overlay networks and study its performance in terms of throughput. We assume that the multicast distribution tree is built at the application level and that each overlay network node has a limited bu#er for packet storage. The overlay MCC decomposes the feedback loop between receivers and sender into a chain of control loops, one for each branch of the multicast distribution tree. To calculate the throughput of a multicast session, we use a linear recurrence method based on the max-plus algebra. Preliminary numerical results demonstrate that the throughput performance of overlay MCC is almost independent of the number of receivers, while for the end-toend MCC, the throughput decreases logarithmically with the number of receivers. This result is a clear indication that overlay networks for multicast distribution o#er a major performance advantage over native end-to-end multicast distribution.

Congestion control protocols rely on receivers to support fair bandwidth sharing. However, a receiver has incentives to elicit self-bene cial bandwidth allocations and hence may manipulate its congestion control protocol. Whereas the issue of receiver misbehavior has been studied for unicast congestion control, the impact of receiver misbehavior in multicast remains unexplored. In this paper, we examine the problem of fair congestion control in distrusted multicast environments. We classify standard mechanisms for multicast congestion control and determine their potential vulnerabilities to receiver misbehavior. Our evaluation of prominent multicast protocols shows that each of them is susceptible to attacks by a misbehaving receiver.

In recent years, much work has been done on attempting to scale multicast data transmission to hundreds or thousands of receivers. In today’s Grid environments, however, a typical application might involve bulk data transfer to just ten or twenty sites. Using multicast for this type of application can provide significant benefits including reduced load on the transmitter, an overall reduction in network traffic, and consequently shorter data transfer times. In this project, we are investigating how multicast can be exploited within such an environment without requiring major changes to applications or underlying networks. The approach taken is to modify TCP to support multicast transfers, and run this modified TCP engine over UDP as a userspace transport protocol. We describe the work to date on the design and implementation, and provide some early experimental results. 1