Vegas is a new implementation of TCP that achieves between 40 and 70 % better throughput, with one-fifth to onehalf the losses, as compared to the implementation of TCP in the Reno distributionof BSD Unix. This paper motivates and describes the three key techniques employed by Vegas, and presents the results of a comprehensive experimental performance study—using both simulations and measurements on the Internet—of the Vegas and Reno implementations of TCP. 1

We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm. In this system sources select transmission rates that maximize their own benefits, utility minus bandwidth cost, and network links adjust bandwidth prices to coordinate the sources' decisions. We allow feedback delays to be different, substantial and time-varying, and links and sources to update at different times and with different frequencies. We provide asynchronous distributed algorithms and prove their convergence in a static environment. We present measurements obtained from a preliminary prototype to illustrate the convergence of the algorithm in a slowly time-varying environment.

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Vegas is an implementation of TCP that achieves between 37 and 71 % better throughput on the Internet, with one-fifth to one-half the losses, as compared to the implementation of TCP in the Reno distribution of BSD Unix. This paper motivates and describes the three key techniques employed by Vegas, and presents the results of a comprehensive experimental performance study—using both simulations and measurements on the Internet—of the Vegas and Reno implementations of TCP.

In this paper we evaluate the effectiveness of Random Early Detection (RED) over traffic types categorized as nonadaptive, fragile and robust, according to their responses to congestion. We point out that RED allows unfair bandwidth sharing when a mixture of the three traffic types shares a link. This unfairness is caused by the fact that at any given time RED imposes the same loss rate on all flows, regardless of their bandwidths. We propose Flow Random Early Drop (FRED), a modified version of RED. FRED uses per-active-flow accounting to impose on each flow a loss rate that depends on the flow's buffer use. We show that FRED provides better protection than RED for adaptive (fragile and robust) flows. In addition, FRED is able to isolate non-adaptive greedy traffic more effectively. Finally, we present a "two-packet-buffer" gateway mechanism to support a large number of flows without incurring additional queueing delays inside the network. These improvements are demonstrated by simulation of TCP and UDP traffic. FRED

In this paper, we demonstrate the existence of fair end-to-end window-based congestion control protocols for packetswitched networks with first come-first served routers. Our definition of fairness generalizes proportional fairness and includes arbitrarily close approximations of max-min fairness. The protocols use only information that is available to end hosts and are designed to converge reasonably fast. Our study is based on a multiclass fluid model of the network. The convergence of the protocols is proved using a Lyapunov function. The technical challenge is in the practical implementation of the protocols.

This paper examines the performance of TCP/IP, the Internet data transport protocol, over Wide Area Networks (WANs) in which data traffic could coexist with real-time traffic such as voice and video. Specifically, we attempt to develop a basic understanding, using analysis and simulation, of the properties of TCP/IP in a regime where (1) the bandwidth-delay product of the network is high compared to the buffering in the network, and (2) there may be transient congestion due to fluctuations in real-time traffic, modeled here as producing random losses among the packets of the TCP connection of interest. The following key results are obtained. First, random loss leads to significant throughput deterioration when the product of the loss probability and the square of the bandwidth-delay product is larger than one. Unless network resources are specifically reserved for data traffic, data traffic will inevitably incur random losses due to transient fluctuations in higher priority real-time traffic when the network is highly utilized. Second, for multiple connections sharing a bottleneck link, TCP is grossly unfair towards connections with higher round-trip delays. This means that a simple First In First Out (FIFO) queueing discipline might not suffice for data traffic in WANs. Finally, we observe that, while the recent Reno version of TCP produces less bursty traffic than the original Tahoe version, it is less robust than the latter when successive losses are closely spaced. We conclude by indicating modifications that may be required both at the transport and network layers to provide good end-to-end performance over high-speed WANs.

This paper presents the “allocated-capacity” framework for providing different levels of best-effort service in times of network congestion. The “allocatedcapacity” framework—extensions to the Internet protocols and algorithms—can allocate bandwidth to different users in a controlled and predictable way during network congestion. The framework supports two complementary ways of controlling the bandwidth allocation: sender-based and receiver-based. In today’s heterogeneous and commercial Internet the framework can serve as a basis for charging for usage and for more efficiently utilizing the network resources. We focus on algorithms for essential components of the framework: a differential dropping algorithm for network routers and a tagging algorithm for profile meters at the edge of the network for bulk-data transfers. We present simulation results to illustrate the effectiveness of the combined algorithms in controlling transmission control protocol (TCP) traffic to achieve certain targeted sending rates.

Network protocols are usually tested in operational networks or in simulated environments. With the former approach it is not easy to set and control the various operational parameters such as bandwidth, delays, queue sizes. Simulators are easier to control, but they are often only an approximate model of the desired setting, especially for what regards the various traffic generators (both producers and consumers) and their interaction with the protocol itself. In this paper we show how a simple, yet flexible and accurate network simulator -- dummynet -- can be built with minimal modifications to an existing protocol stack, allowing experiments to be run on a standalone system. dummynet works by intercepting communications of the protocol layer under test and simulating the effects of finite queues, bandwidth limitations and communication delays. It runs in a fully operational system, hence allowing the use of real traffic generators and protocol implementations, while solving the prob...

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.