Queue Management for the Heavy-Tailed Traffics (original) (raw)

Simulation of an Active Queue Management in a Quality of Service Internet Using Random Early Detection (Red)

This paper work presents simulation of an active queue management in a quality of service Internet using differentiated service random early detection (DiffServ RED) algorithm for congestion avoidance in packet switched network. RED algorithm is designed to accompany a transport­layer congestion control protocol such as TCP. We explored how the algorithm, earlier designed by [8], could be used to achieve differential packet dropping required by real­time traffic in the extended TCP/IP protocol for the Internet. The queue manager operates by setting thresholds (minimum and maximum) for the average queue size to detect incipient congestion. When the average queue size is below the minimum threshold, all arriving packets are properly enqueued for dispatch to their destinations. Any time the average queue size exceeds a preset minimum thresholds, the gateway drops packets at random or marks each arriving packet with a certain probability, where the exact probability is a function of the...

Comparison of tail drop and active queue management performance for bulk-data and web-like Internet traffic

… IEEE Symposium on, 2001

queue management mechanism: RED with a standard parameter setting, RED with an optimized parameter setting based on a model of RED with TCP flows, and finally a version of RED with a smoother drop function called "gentle RED". Performance is evaluated under various load situations for FTP-like and Web-like flows, respectively. We use measurements and simulations to evaluate the performance of the queue management mechanisms and assess their impact on a set of operator oriented performance metrics. We find that in total (i) no performance improvements of RED compared to Tail Drop can be observed; (ii) fine tuning of RED parameters is not sufficient to cope with undesired RED behavior due to the variability in traffic load; (iii) gentle RED is capable of resolving some of the headaches on RED but not all.

A study of deploying smooth- and responsive-TCPs with different queue management schemes

International Journal of Communication Systems, 2009

While there exist extensive research works on congestion control and active queue management, or the joint dynamics of a congestion control strategy with the Random Early Detection (RED) algorithm, little has been done on the interactions between different window adjustment strategies and different queue management schemes such as DropTail and RED. In this paper, we consider a spectrum of TCP-friendly Additive Increase and Multiplicative Decrease (AIMD) parameters. At the one end of this spectrum, smooth TCP enhances smoothness for multimedia applications by reducing the window decrease ratio upon congestion, at the cost of the additive increase speed and the responsiveness to available bandwidth. At the other end, responsive TCP enhances the responsiveness by increasing the additive increase speed, at the cost of smoothness. We investigate the network dynamics with various combinations of AIMD parameters and queue management schemes, under different metrics. The investigation is conducted from the deployment (especially incremental deployment) point of view. We discussed the impact of the interactions on the goodput, fairness, end-to-end delay, and its implications to energy-consumption on mobile hosts.

Revisiting the Gentle Parameter of the Random Early Detection (RED) for TCP Congestion Control

-The Random Early Detection (RED) is used as an Active Queue Management (AQM) Technique for TCP congestion handling. A modification of RED called the Gentle RED (GRED) has been proposed by adding the Gentle parameter to the original implementation of RED. This parameter has been turned on by default in the NS2 simulator versions 2.1b and later; claiming that it helps in smoothing out traffic in routers and increases network performance. In this article we revisit this parameter and show, through simulation, that this parameter should be turned off in current simulations of RED using the NS2 simulator and it should be replaced by any adaptation parameter such as the Adaptive parameter in ARED.

A Comparative Analysis of Queue Management Techniques using NS-2 Simulator

Effectively and fairly allocating resources to the competing users in a network is a major issue to meet the demand for higher performance nowadays. Queue management enhances the efficiency of transfers and cooperates with Transmission Control Protocol (TCP) in adapting the intense flow of the congestion in the network. The shared resources of a network are bandwidth of the link and queues on the routers and switches. As too many packets are queued awaiting transmission, the queues overflow and the packets have to be dropped which results into congestion. The queue management algorithm, which is applied to a router, plays an important role in providing Quality of Service (QoS). In this paper, we have presented a simulation based comparison and evaluation of four popular queue management schemes: Stochastic Fair Queuing (SFQ), Random Early Detection (RED), Random Exponential Marking (REM) and Droptail in terms of packet drop rate and delay. Simulation is done using Network Simulator (ns2.34) Our Simulation results indicate that REM performed better in terms of packet drop rate and RED performs better in terms of end-to-end delay.

Random Early Discard (RED) Queue Evaluation for Congestion Control

Reinventing the Web

Congestion is an un-avoiding issue of networking, and many attempts and mechanisms have been devised to avoid and control congestion in diverse ways. Random Early Discard (RED) is one of such type of algorithm that applies the techniques of Active Queue Management (AQM) to prevent and control congestion and to provide a range of Internet performance facilities. In this chapter, performance of RED algorithm has been measured from different point of views. RED works with Transmission Control Protocol (TCP), and since TCP has several variants, the authors investigated which versions of TCP behave well with RED in terms of few network parameters. Also, performance of RED has been compared with its counterpart Drop Tail algorithm. These statistics are immensely necessary to select the best protocol for Internet performance optimization.

Efficient Queue Management for TCP Flows

2001

Packets in the Internet can experience large queueing delays during busy periods. Backbone routers are generally engineered to have large buffers, in which packets may wait as long as half a second (assuming FIFO service, longer otherwise). During congestion periods, these buffers may stay close to full, subjecting packets to long delays, even when the intrinsic latency of the path is relatively small. This paper studies the performance improvements that can be obtained by using more sophisticated packet schedulers, than are typical of Internet routers. The results show that the large buffers found in WAN routers contribute only marginally to improving router throughput, and the higher delays that come with large buffers makes them a dubious investment. The results also show that better packet scheduling algorithms can produce dramatic improvements in fairness. Using ns-2 simulations, we show that algorithms using multiple queues can significantly outperform RED and Blue, especially at smaller buffer sizes. Over a single-bottleneck link, the variance in TCP goodput using the proposed multiqueue packet schedulers is one-tenth that obtained with RED and one-fifth that obtained with Blue. Given a traffic mix of TCP flows with different roundtrip times, longer round-trip time flows achieve ¢ ¡ ¤ £ of their fair-share using multiqueue schedulers, compared to ¥ ¡ ¤ £ under RED and Blue. We observe a similar performance improvement for multi-hop paths.

TCP – Random Early Detection (RED) mechanism for Congestion Control

2015

This thesis discusses the Random Early Detection (RED) algorithm, proposed by Sally Floyd, used for congestion avoidance in computer networking, how existing algorithms compare to this approach and the configuration and implementation of the Weighted Random Early Detection (WRED) variation. RED uses a probability approach in order to calculate the probability that a packet will be dropped before periods of high congestion, relative to the minimum and maximum queue threshold, average queue length, packet size and the number of packets since the last drop.

Performance Comparison of Active Queue Management Techniques

Journal of Computer Science, 2008

Congestion is an important issue which researchers focus on in the Transmission Control Protocol (TCP) network environment. To keep the stability of the whole network, congestion control algorithms have been extensively studied. Queue management method employed by the routers is one of the important issues in the congestion control study. Active Queue Management (AQM) has been proposed as a router-based mechanism for early detection of congestion inside the network. In this study, we are comparing AQM two popular queue management methods, Random Early Detection (RED) and droptail, in different aspects, such as throughput and fairness Index. The comparison results indicate RED performed slightly better with higher throughput and higher fairness Index than droptail. Simulation is done by using Network Simulator (NS 2) and the graphs are drawn using X-graph.

An Experimental Analysis of Random Early Discard (RED) Queue for Congestion Control

2011

Active Queue Management (AQM) is receiving wide attention as a promising technique to prevent and avoid congestion collapse in packet-switched networks. By providing advanced warning of incipient congestion, end nodes can respond to congestion before router buffer overflows and hence ensure improved performance. Random Early Discard (RED) is an IETF recommended active queue management scheme that is expected to provide several Internet performance advantages such as minimizing packet loss and router queuing delay, avoiding global synchronization of sources, guaranteeing high link utilization and fairness. It tends to drop packets from each connection in proportion to the transmission rate the flow has on the output link. It does not minimize the number of dropped packets as expected, but it manages to achieve improved performance when compared to the Tail Drop. In this paper, extensive experimental analysis has been carried out on RED using Network Simulator (NS-2) in relation to congestion control and decision has been settled where RED can perform better.