In this paper we use jump process driven Stochastic Differential Equations to model the interactions of a set of TCP flows and Active Queue Management routers in a network setting. We show how the SDEs can be transformed into a set of Ordinary Differential Equations which can be easily solved numerically. Our solution methodology scales well to a large number of flows. As an application, we model and solve a system where RED is the AQM policy. Our results show excellent agreement with those of similar networks simulated using the well known ns simulator. Our model enables us to get an in-depth understanding of the RED algorithm. Using the tools developed in this paper, we present a critical analysis of the RED algorithm. We explain the role played by the RED configuration parameters on the behavior of the algorithm in a network. We point out a flaw in the RED averaging mechanism which we believe is a cause of tuning problems for RED. We believe this modeling/solution methodology has a great potential in analyzing and understanding various network congestion control algorithms.

In this work, we investigate mechanisms for Internet congestion control in general, and Random Early Detection (RED) in particular. We first study the current proposals for RED implementation and identify several structural problems such as producing large traffic oscillations and introducing unnecessary overhead in the fast path forwarding. We model RED as a feedback control system and we discover fundamental laws governing the traffic dynamics in TCP/IP networks. Based on this understanding, we derive a set of recommendations for the architecture and implementation of congestion control modules in routers, such as RED. I. INTRODUCTION Congestion control for IP networks has been a recurring problem for many years. The problem of congestion collapse encountered by early TCP/IP protocols has prompted the study of end-to-end congestion control algorithms in the late 80's and proposals such as [4], which forms the basis for the TCP congestion control in current implementations. The ess...

In order to stem the increasing packet loss rates caused by an exponential increase in network traffic, the IETF is considering the deployment of active queue management techniques such as RED [13]. While active queue management can potentially reduce packet loss rates in the Internet, this paper shows that current techniques are ineffective in preventing high loss rates. The inherent problem with these queue management algorithms is that they all use queue lengths as the indicator of the severity of congestion.

Blue(SFB), a novel technique for enforcing fairness among a large number of flows. SFB scalably detects and rate-limits non-responsive flows through the use of a marking probability derived from the BLUE queue management algorithm and a Bloom filter. Using analysis and simulation, SFB is shown to effectively handle non-responsive flows using an extremely small amount of state information.

In active queue management (AQM), core routers signal transmission control protocol (TCP) sources with the objective of managing queue utilization and delay. It is essentially a feedback control problem. Based on a recently developed dynamic model of TCPs congestion-avoidance mode, this paper does three things. First, it relates key network parameters such as the number of TCP sessions, link capacity and round-trip time to the underlying feedback control problem. Second, it analyzes the present de facto AQM standard: random early detection (RED) and determines that REDs queue-averaging is not beneficial. Finally, it recommends alternative AQM schemes which amount to classical proportional and proportional-integral control. We illustrate our results using ns simulations and demonstrate the practical impact of proportional-integral control on managing queue utilization and delay.

We demonstrate that the dynamic behavior of queue and average window is determined predominantly by the stability of TCP/RED, not by AIMD probing nor noise traffic. We develop a general multi-link multi-source model for TCP/RED and derive a local stability condition in the case of a single link with heterogeneous sources. We validate our model with simulations and illustrate the stability region of TCP/RED. These results suggest that TCP/RED becomes unstable when delay increases, or more strikingly, when link capacity increases. The analysis illustrates the difficulty of setting RED parameters to stabilize TCP: they can be tuned to improve stability, but only at the cost of large queues even when they are dynamically adjusted. Finally, we present a simple distributed congestion control algorithm that maintains stability for arbitrary network delay, capacity, load and topology.

In order to stem the increasing packet loss rates caused by an exponential increase in network traffic, the IETF has been considering the deployment of active queue management techniques such as RED [14]. While active queue management can potentially reduce packet loss rates in the Internet, we show that current techniques are ineffective in preventing high loss rates. The inherent problem with these queue management algorithms is that they use queue lengths as the indicator of the severity of congestion. In light of this observation, a fundamentally different active queue management algorithm, called BLUE, is proposed, implemented and evaluated. BLUE uses packet loss and link idle events to manage congestion. Using both simulation and controlled experiments, BLUE is shown to perform significantly better than RED both in terms of packet loss rates and buffer size requirements in the network. As an extension to BLUE, a novel technique based on Bloom filters [2] is described for enforcing fairness among a large number of flows. In particular, we propose and evaluate Stochastic Fair BLUE (SFB), a queue management algorithm which can identify and rate-limit non-responsive flows using a very small amount of state information. I.

We demonstrate that the dynamic behavior of queue and average window is determined predominantly by the stability of TCP/RED, not by AIMD probing nor noise tra#c. We develop a general multi-link multi-source model for TCP/RED and derive a local stability condition in the case of a single link with heterogeneous sources. We validate our model with simulations and illustrate the stability region of TCP/RED. These results suggest that TCP/RED becomes unstable when delay increases, or more strikingly, when link capacity increases. The analysis illustrates the di#culty of setting RED parameters to stabilize TCP: they can be tuned to improve stability, but only at the cost of large queues even when they are dynamically adjusted.

Abstract—This paper describes the results of the first comprehensive analysis of a range of popular on-line, multiplayer, game servers. The results show that the traffic behavior of these servers is highly predictable and can be attributed to the fact that current game designs target the saturation of the narrowest, last-mile link. Specifically, in order to maximize the interactivity of the game itself and to provide relatively uniform experiences between players playing over different network speeds, on-line games typically fix their usage requirements in such a way as to saturate the network link of their lowest speed players. While the traffic observed is highly predictable, the traces also indicate that these on-line games provide significant challenges to current network infrastructure. As a result of synchronous game logic requiring an extreme amount of interactivity, a close look at the trace reveals the presence of large, highly periodic, bursts of small packets. With such stringent demands on interactivity, routers must be designed with enough capacity to quickly route such bursts without delay. Index Terms—Communication system traffic, games, measurement, network servers, networks.

Random Early Detection (RED) is the recommended active queue management scheme for rapid deployment throughout the Internet. As a result, there have been considerable research efforts in studying the performance of RED. However, previous studies have often focused on relatively homogeneous environment. The effects of RED in a heterogeneous environment are not thoroughly understood. In this paper, we use extensive simulations to explore the interaction between RED and various types of heterogeneity, as well as the impact of such interaction on the user-perceived end-to-end performance. Our results show that overall RED improves performance at least for the types of heterogeneity we have considered.