Advances in Active Queue Management (AQM) Based TCP Congestion Control (original) (raw)

A novel self-tuning feedback controller for active queue management supporting TCP flows

Information Sciences, 2010

Wireless access points act as bridges between wireless and wired networks. Since the actually available bandwidth in wireless networks is much smaller than that in wired networks, there is a bandwidth disparity in channel capacity which makes the access point a significant network congestion point. The recently proposed active queue management (AQM) is an effective method used in wired network and wired-wireless network routers for congestion control, and to achieve a tradeoff between channel utilization and delay. The de facto standard, the random early detection (RED) AQM scheme, and most of its variants use average queue length as a congestion indicator to trigger packet dropping. In this paper, we propose a Novel autonomous Proportional and Differential RED algorithm, called NPD-RED, as an extension of RED. NPD-RED is based on a self-tuning feedback proportional and differential controller, which not only considers the instantaneous queue length at the current time point, but also takes into consideration the ratio of the current differential error signal to the buffer size. Furthermore, we give theoretical analysis of the system stability and give guidelines for the selection of feedback gains for the TCP/RED system to stabilize the instantaneous queue length at a desirable level. Extensive simulations have been conducted with ns2. The simulation results have demonstrated that the proposed NPD-RED algorithm outperforms the existing AQM schemes in terms of average queue length, average throughput, and stability.

Active Queue Management in TCP networks based on Nonlinear Generalized Minimum Variance control

The 2nd International Conference on Control, Instrumentation and Automation, 2011

We introduce a novel and robust active queue management (AQM) scheme based on a fuzzy controller, called hybrid fuzzy-PID controller. In the TCP network, AQM is important to regulate the queue length by passing or dropping the packets at the intermediate routers. RED, PI, and PID algorithms have been used for AQM. But these algorithms show weaknesses in the detection and control of congestion under dynamically changing network situations. In this paper a novel Fuzzy-based proportional-integral derivative (PID) controller, which acts as an active queue manager (AQM) for Internet routers, is proposed. These controllers are used to reduce packet loss and improve network utilization in TCP/IP networks. A new hybrid controller is proposed and compared with traditional RED based controller. Simulations are carried out to demonstrate the effectiveness of the proposed method and show that, the new hybrid fuzzy PID controller provides better performance than random early detection (RED) and PID controllers.

Active queue management algorithm with a rate regulator

Proceedings of the 15th IFAC World Congress, 2002, 2002

In this paper, we propose an efficient control scheme for active queue management (AQM) supporting TCP flows. The proposed controller consists of two parts: a rate controller and a queue size controller. The rate controller is a proportional-integral (PI) controller, which improves the response to dynamic traffic variation and keeps the packet arrival rate around the link capacity. The queue size controller is a proportional (P) controller like the Random Early Detection (RED) algorithm. The rate controller gains are obtained by minimizing the performance index, either the integral square error (ISE) or the integral absolute error (IAE). We compare the performances of the proposed algorithm, the RED algorithm and the PI controller for AQM through ns simulations.

Anti-windup compensator for active queue management in TCP networks

Control Engineering Practice, 2003

In this paper, we apply a dynamic anti-windup scheme for improving the performance of a conventional proportional-integral (PI) controller for active queue management (AQM) supporting TCP flows. When a PI controller is used for AQM, the windup phenomenon of the integral action can cause performance degradation because the packet drop probability is limited between 0 and 1. Therefore we suggest a TCP/AQM model with a saturating actuator and apply a dynamic anti-windup method for improving the performance of the conventional PI AQM scheme. The proposed scheme not only provides graceful performance degradation, but also guarantees the stability of the overall system with the linearized TCP model. We verify the performance of the proposed scheme through ns-2 simulations. The simulation results show that our scheme outperforms the conventional PI controller when the traffic load is not stationary, which is always the case in real network environment. r

A novel congestion control protocol with AQM support for IP-based networks

Telecommunication Systems, 2013

Multimedia services (Real-time and Non realtime) have different demands, including the need for high bandwidth and low delay, jitter and loss. TCP is a dominant protocol on the Internet. In order to have the best performance in TCP, the congestion window size must be set according to some parameters, since the TCP source is not aware of the window size. TCP emphasizes more on reliability than timeliness, so TCP is not suitable for real-time traffic. In this paper an active Queue management support TCP (QTCP) model is presented. Source rate is regulated based on the feedback which is received from intermediate routers. Furthermore, in order to satisfy the requirements of multimedia applications, a new Optimization Based active Queue management (OBQ) mechanism has been developed. OBQ calculates packet loss probabilities based on the queue length, packets priority and delay in routers and the results are sent to source, which can then regulate its sending rate. Simulation results indicate that the QTCP reduces packet loss and buffer size in intermediate nodes, improves network throughput and reduces delay.

Adaptive optimization for active queue management supporting TCP flows

2016 American Control Conference (ACC), 2016

An adaptive decentralized strategy for active queue management of TCP flows over communication networks is presented. The proposed strategy solves locally, at each link, an optimal control problem, minimizing a cost composed of residual capacity and buffer queue size. The solution of the optimal control problem exploits an adaptive optimization algorithm aiming at adaptively minimizing a suitable approximation of the Hamilton-Jacobi-Bellman equation associated with the optimal control problem. Simulations results, obtained by using a fluid flow based model of the communication network and a common network topology, show improvement with respect to the Random Early Detection strategy. Besides, it is shown that the performance of the proposed decentralized solution is comparable with the performance obtained with a centralized strategy, which solves the optimal control problem via a central unit that maintains the flow states of the entire network.

Robust TCP Packets Queue Control

1st IFAC Workshop on Estimation and Control of Networked Systems, 2009

This paper is concerned with the control of network data transfer so as to avoid internet traffic congestion. Specifically, a new Active Queue Management (AQM) algorithm supporting the Transmission Control Protocol (TCP) is suggested. To this purpose, the TCP dynamics is described by means of a second-order model with delayed input obtained from the linearization of an efficient nonlinear fluid-based model. By applying the Artstein transformation, the input-delayed model is first reduced to a delay-free model. Then, a feedback AQM controller is designed for this model using a Sliding Mode Control (SMC) strategy. Simulation results show the effectiveness of the proposed AQM technique.

Comparative performance analysis of TCP-based congestion control algorithms

International Journal of Communication Networks and Distributed Systems, 2016

In order to curtail the escalating packet loss rates caused by an exponential increase in network traffic, active queue management techniques such as Random Early Detection (RED) have come into picture. Flow Random Early Drop (FRED) keeps state based on instantaneous queue occupancy of a given flow. FRED protects fragile flows by deterministically accepting flows from low bandwidth connections and fixes several shortcomings of RED by computing queue length during both arrival and departure of the packet. Stochastic Fair Queuing (SFQ) ensures fair access to network resources and prevents a busty flow from consuming more than its fair share. In case of (Random Exponential Marking) REM, the key idea is to decouple congestion measure from performance measure (loss, queue length or delay). Stabilized RED (SRED) is another approach of detecting nonresponsive flows. In this paper, we have shown a comparative analysis of throughput, delay and queue length for the various congestion control algorithms RED, SFQ and REM. We also included the comparative analysis of loss rate having different bandwidth for these algorithms.

Aggregate Rate Control for Efficient and Practical Congestion Managment

2004

Active queue management (AQM) promises to overcome the current limitations of end-host only congestion control by providing congestion feedback information before router queue buffers overflow. Many emerging AQM approaches use proportional integral (PI) controller design because of PI's simplicity and effectiveness. Unfortunately, these promising AQMs still face a critical deployment challenge since there are no simple and effective PI control parameter configurations available for time-delayed systems (i.e. the Internet). As a solution, we present the Aggregate Rate Controller (ARC), a reduced parameter PI controller for Internet traffic. ARC, founded on both classical control theory and a sound understanding of Internet congestion control, uses a low frequency rate-based approach to detect congestion that minimizes control noises and provides more flexible link Quality of Service (QoS) compared with queue-based approaches. In addition, we provide practical configuration guidelines for ARC that produce efficient and resilient performance over a wide range of traffic conditions. Simulations verify that ARC effectively handles network congestion over a range of network and traffic conditions, overall outperforming other mechanisms in terms of queue dynamics, link utilization, data loss rate and object response time for Web traffic.

Active Queue Management For Transmission Congestion control

PIJMT, 2015

Computer networks is defined as network, which consists of one or more computers or any other devices like routers, switches, hub, server etc. that are linked together to interact to each other and shares data and other resources. The devices on the network are referred to as nodes. These nodes communicate with each other using medium such as twisted pair cable, Ethernet cable, Optical fiber cables and radio waves and they all can be arranged according to various topologies such as bus, ring, tree etc. Computer networks have gone through a sudden growth over the past few years and with that growth have come severe congestion problems. Internet congestion occurs as the demand increases than available resources. The congestion creates many problems like data loss, long delay, waste of resources and much more. It has a huge influence to both wired network and wireless network and causes the problem of packet loss, packet delay and lock out. To control congestion there are many techniques, such as exponential back off, congestion control in TCP, priority schemes and queue management.  Exponential back off is used in CSMA/CA which is sensing scheme of 802.11. The sender senses the channel before transmission. If the channel is busy it wait until idle and sends the data after a random period of time. The random period is calculated by exponential back off.  Congestion control in TCP consists of slow start, fast transmission, fast recovery, congestion avoidance [1]. It is a method to controlling the transmission rate of the sender. The TCP flows starts at a very slow rate and increase exponentially to a threshold. Congestion avoidance then happens and congestion window increases by one segment each time for one successful transmission. Congestion control in TCP defines TCP's four intertwined congestion control algorithms: slow start, congestion avoidance, fast retransmit, and fast recovery.  Priority queues marks the packets into different priorities and drops low priority packets when it is needed. It is not a real congestion control method but improves the performance with other methods. 3 www.pijmt.com  Queue management is a way to control the queue size of the bottlenecks. It contains passive queue management, which drops packet when the queue is full and active  queue management which drops the packets before buffer getting full. Drop Tail and random Early Detection (RED) are algorithms that represent the two ways respectively. RED is more complicated but can avoid congestion and lockout.