Congestion Control In High-speed Networks Research Articles

Hybrid congestion control for high-speed networks

Nowadays, more and more applications require fast transfer of massive data over networks, and the emergence of high-speed networks provides an ideal solution to this challenge. Due to the limitations of the conservative congestion control algorithm, the standard TCP is no longer appropriate for high-speed networks to efficiently utilize the bandwidth resources. Therefore, several high-speed TCP variants have been suggested to conquer the problem. However, although these protocols perform successfully to improve the bandwidth utilization, they still have the weakness on the performance such as RTT-fairness, TCP-friendliness, etc. In this paper, we propose HCC TCP, a hybrid congestion control algorithm using the synergy of delay-based and loss-based approach for the adaptation to high speed and long distance network environment. The algorithm uses queuing delay as the primary congestion indicator, and adjusts the window to stabilize around the size which can achieve the full utilization of available bandwidth. On the other hand, it uses packet loss as the second congestion indicator, and a loss-based congestion control strategy is utilized to maintain high bandwidth utilization in the cases that the delay-based strategy performs inefficiently in the networks. The two approaches in the algorithm are dynamically transferred into each other according to the network status. We finally perform simulations to verify the properties of the proposed HCC TCP. The simulation results demonstrate HCC TCP satisfies the requirements for an ideal TCP variant in high-speed networks, and achieves efficient performance on throughput, fairness, TCP-friendliness, robustness, etc.

Unreliable transport protocol using congestion control for high-speed networks

Currently there is no control for the real-time traffic of multimedia applications using UDP (User Datagram Protocol) in high-speed networks. Therefore, although a number of high-speed TCP (Transmission Control Protocol) protocols have been developed for gigabit-speed (or faster) links, the real-time traffic could also congest the network and result in unfairness and throughput degradation of TCP traffic. In this paper, a new unreliable transport protocol, FAST DCCP, is presented for the real-time traffic in high-speed networks. FAST DCCP is based on the DCCP protocol and adopts the FAST scheme to realize congestion control. Some modifications have been made to the mechanisms inherited from DCCP so as to let the proposed protocol can efficiently operate under a large size window. In addition, an enhanced protocol, EEFAST DCCP, using the measurements of one-way delay to dynamically adjust the window size is also proposed to improve the throughput of FAST DCCP with the effect of reverse traffic. Simulation results show that FAST DCCP not only can satisfy the requirements of real-time data delivery, but also perform well in bandwidth utilization and fairness in high-speed networks. Meanwhile, EEFAST DCCP is able to effectively conquer the throughput degradation caused by the reverse traffic.

Cooperative Multiagent Congestion Control for High-Speed Networks

An adaptive multiagent reinforcement learning method for solving congestion control problems on dynamic high-speed networks is presented. Traditional reactive congestion control selects a source rate in terms of the queue length restricted to a predefined threshold. However, the determination of congestion threshold and sending rate is difficult and inaccurate due to the propagation delay and the dynamic nature of the networks. A simple and robust cooperative multiagent congestion controller (CMCC), which consists of two subsystems: a long-term policy evaluator, expectation-return predictor and a short-term rate selector composed of action-value evaluator and stochastic action selector elements has been proposed to solve the problem. After receiving cooperative reinforcement signals generated by a cooperative fuzzy reward evaluator using game theory, CMCC takes the best action to regulate source flow with the features of high throughput and low packet loss rate. By means of learning procedures, CMCC can learn to take correct actions adaptively under time-varying environments. Simulation results showed that the proposed approach can promote the system utilization and decrease packet losses simultaneously.

Robust stability of some oscillatory systems including time-varying delay with applications in congestion control

Abstract This paper focuses on the stability of some second-order linear systems with multiple constant and time-varying delays, under the assumption that the corresponding system without delays is an oscillator. Sufficient conditions for delay-dependent stability will be derived using the integral quadratic constraint approach combined with the generalized eigenvalue distribution of some appropriate finite-dimensional matrix pencils. As applications, we shall discuss some fluid approximation models used in congestion control of high-speed networks, under the natural assumptions that the control-time intervals are constant, but the round-trip times are time-varying.

Diffusion approximations for a single node accessed by congestion-controlled sources

We consider simple models of congestion control in high-speed networks, and develop diffusion approximations which could be useful for resource allocation. We first show that, if the sources are ON-OFF type with exponential ON and OFF times, then, under a certain scaling, the steady-state distribution of the number of active sources can be described by a combination of two appropriately truncated and renormalized normal distributions. For the case where the source arrival process is Poisson and the service times are exponential, the steady-state distribution consists of appropriately normalized and truncated Gaussian and exponential distributions. We then consider the case where the arrival process is a general renewal process with finite coefficient of variation and service-time distributions that are phase type, and show the impact of these distributions on the steady-state distribution of the number of sources in the system. We also establish an insensitivity to service-time distribution when the arrival process is Poisson. We use these results to relate the capacity of a bottleneck node to performance measures of interest for best effort traffic.

Fuzzy neural network based traffic prediction and congestion control in high-speed networks

Congestion control is one of the key problems in high-speed networks, such as ATM. In this paper, a kind of traffic prediction and preventive congestion control scheme is proposed using neural network approach. Traditional predictor using BP neural network has suffered from long convergence time and dissatisfying error. Fuzzy neural network developed in this paper can solve these problems satisfactorily. Simulations show the comparison among no-feedback control scheme, reactive control scheme and neural network based control scheme.

Traffic modeling, prediction, and congestion control for high-speed networks: a fuzzy AR approach

In this study, a fuzzy autoregressive (fuzzy-AR) model is proposed to describe the traffic characteristics of high-speed networks. The fuzzy-AR model approximates a nonlinear time-variant process with a combination of several linear local AR processes using a fuzzy clustering method. We propose that the use of this fuzzy-AR model has greater potential for congestion control of packet network traffic. The parameter estimation problem in fuzzy-AR modeling is treated by a clustering algorithm developed from actual traffic data in high-speed networks. Based on the adaptive AR-prediction model and queueing theory, a simple congestion control scheme is proposed to provide an efficient traffic management for high-speed networks. Finally, using the actual Ethernet-LAN packet traffic data, several examples are given to demonstrate the validity of this proposed method for high-speed network traffic control.

Statistical multiplexing with loss priorities in rate-based congestion control of high-speed networks

Statistical multiplexing with loss priorities is a central element in ATM-based B-ISDN. Cell priorities arise from the marking schemes employed by the access regulators to identify excess cells, which are dropped during periods of congestion, Also, in real time applications, such as hierarchically coded voice and video, cells are assigned priorities which correspond to their importance to service quality, so that when congestion occurs only the least important are dropped. The authors present a stochastic fluid model of statistical multiplexing with loss priorities. Each Markov modulated fluid source generates streams of different priorities. The burstiness of each stream and the correlation between the priority streams are captured in the mode. The loss priority is implemented by selectively discarding cells of certain priority classes when the buffer content exceeds a corresponding threshold. To handle high dimensional source models, the authors develop an algebraic theory for the efficient computation of the spectrum of the statistical multiplexing system, which generalizes previous results for on-off sources. It is shown that to obtain the solution of the statistical multiplexing problem with J priority classes, J different 1-class problems need to be solved, together with a system of linear equations which describe the behavior of the stationary distribution at the thresholds. The numerical results demonstrate the manner in which i) the threshold level controls the tradeoff between delay of higher priority cells and the loss probability of lower priority cells, and ii) the buffer size controls the loss probability of higher priority cells. >

Congestion control for multimedia services

The problem of congestion control in high-speed networks for multimedia traffic, such as voice and video, is considered. It is shown that the performance requirements of high-speed networks involve delay, delay-jitter, and packet loss. A framing congestion control strategy based on a packet admission policy at the edges of the network and on a service discipline called stop-and-go queuing at the switching nodes is described. This strategy provides bounded end-to-end delay and a small and controllable delay-jitter. The strategy is applicable to packet switching networks in general, including fixed cell length asynchronous transfer mode (ATM), as well as networks with variable-size packets.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>