Nonlinear analysis of RED - a comparative study

Last decade seen an astronomical growth in the development of the multi-hop wireless technologies such as mobile ad-hoc network, vehicular ad-hoc network and cognitive radio network, the network congestion poses a serious threat in full scale deployment of wireless multi-hop technologies towards internet architecture. An active queue management (AQM) is a proactive, effective congestion control mechanism deployed at the intermediate gateway. Random Early Detection (RED) is the earliest and most widely used Active Queue Management (AQM) mechanism in backbone gateways, which in turn reduce global synchronization and bias against burst traffic. The traditional RED and its variants such GRED, AGRED, ARED, NL-RED, REM, RIO, etc. has more parameters to be tuned each time for the arrival of the packet. The tuning of more parameters leads to computation load, so it is unsuitable for low memory less devices such as laptops, handset, etc. In this paper, a micro level analysis was made on standard AQM's under multi-hop wireless environment. The results were analyzed based on the metrics such as average queue length, packet loss, queuing delay, end to end delay and throughput. This work forms a base work in designing a new queuing algorithm over heavily tailed multi-hop networks.

In data communication when there are too many packets contending for the limited shared resources, such as the queue buffer in the router at bottleneck link, it may result in congestion. During congestion, large amount of packets experience delay or even be dropped due to the queue overflow. Severe congestion problems result in degradation of the throughput and large packet loss rate. In this paper, analysis of throughput and packet loss rate for different buffer sizes is presented; taking into account two popular queue management methods, Random Early Detection (RED) and Drop Tail, for different TCP and UDP streams coming to a common router buffer. The results indicate that the throughput and efficiency of TCP increases with increase in buffer size for RED. Moreover, UDP packet loss decreases with an increase in buffer size while the buffer size has no key impact on UDP packet delays. Simulation has been done by using Network Simulator (NS2-2.37) and the graphs are plotted using GNU plot.

Random Early Detection (RED) is one of the most commonly used Active Queue Management (AQM) algorithms that is recommended by IETF for deployment in the network. Although RED provides low average queuing delay and high throughput at the same time, but effectiveness of RED is highly sensitive to the RED parameters setting. As network condition varies largely, setting RED's parameters with fixed values is not an efficient solution. We propose a new method to dynamically tuning RED's parameters. For this purpose, we compute the rate of which the queue is occupied and consider it as a congestion metric that will be forecasted when the queue is overloaded. This meter is used to dynamically setting RED parameters. The simulation results show the effectiveness of the proposed method. According to the results, we achieve a significantly higher utilization and less packet loss comparing to original RED algorithm in dynamic conditions of the network.

We present a virtual queue-based active queue management (AQM) scheme, called stabilized virtual buffer (SVB). The SVB scheme uses the packet arrival rate and queue length information to drop/mark packets probabilistically in a congested Internet router. System goodput, packet loss rate, average queue length, and stability of the queue are used to compare the proposed SVB scheme with prior AQM schemes (RED - random early detection; REM - random exponential marking; AVQ - adaptive virtual queue). Simulation results indicate that the SVB algorithm can provide better goodput and lower loss rate than the other three AQMs. The most striking feature of the proposed scheme is its robustness to workload fluctuations in maintaining a stable queue for different workload mixes (short and long flows) and parameter settings.

In this paper we address the issue of cross-layer design in transport layer enhancement mechanisms, where the data-link and transport layer information is shared with each other, in order to provide improved system throughput of the wireless cellular network. We propose a cross-layer transport layer enhancement mechanism with name of XST (cross-layer snoop protocol for TCP), which is based on Snoop protocol combined with the forced duplicate acknowledgement congestion control strategy in wireless cellular networks. XST employs the cross-layer design, working at the data-link layer but using the transport layer information as operating criteria. We conduct a comparative study between the XST mechanism and active queue management (AQM) mechanism in the literature, such as random early detection (RED) in wireless environments with varying link characteristics. Simulation results demonstrate that the proposed XST significantly outperforms RED in wireless cellular network, especially under high-error-rate which is a major characteristic of wireless links.

The explosive increase in the volume and variety of Internet traffic has placed a growing emphasis on congestion control and fairness in Internet routers. Approaches to the problem of congestion, such as active queue management schemes like Random Early Detection (RED) use congestion avoidance techniques and are successful with TCP flows. Approaches to the problem of fairness, such as Fair Random Early Drop (FRED), keep per-flow state and punish misbehaved, non-TCP flows. Unfortunately, these punishment mechanisms also result in a significant performance drop for multimedia flows that use flow control. We extend Class-Based Threshold (CRT) [12], and propose a new active queue management mechanism as an extension to RED called Dynamic Class-Based Threshold (D- CBT) to improve multimedia performance on the Internet. Also, as an effort to reduce multimedia jitter, we propose a lightweight packet scheduling called Cut-In Packet Scheduling (ChIPS) as an alternative to FIFO packet scheduling. The performance of our proposed mechanisms is measured, analyzed and compared with other mechanisms (RED and CBT) in terms of throughput, fairness and multimedia jitter through simulation using NS. The study shows that D-CBT improves fairness among different classes of flows and ChIPS improves multimedia jitter without degrading fairness.

In Internet gateways with active queue management, effective algorithms are often used to enhance the traffic flows through the gateway. The random early detection (RED) algorithm is a widely used algorithm for controlling the transmission control protocol (TCP) flows. Specifically, the RED algorithm has deliberately introduced randomness into the explicit congestion notification (ECN) marking mechanism in order to enhance the fairness and to avoid synchronization of TCP flows through the gateway. As randomness plays a key role in providing better performance for RED gateways than the DropTail gateways, knowledge of the effect of the random mechanism is important to the understanding the behavior of the system. The fluid flow model (FFM), ignoring the randomness of ECN markings, has provided a fast alternative to the slow ns-2 network simulation tool in studying the TCP flow in the RED gateway. In this brief, the random ECN marking mechanism in RED gateways has been studied. The randomness of the RED ECN marking algorithm is implemented into the FFM. Verified using ns-2 simulations, the proposed model shows better dynamical performance than FFM in both the single-bottleneck dumbbell network and in networks with interactive bottlenecks.

Congestion is a key topic in computer networks that has been studied extensively by scholars due to its direct impact on a network’s performance. One of the extensively investigated congestion control techniques is random early detection (RED). To sustain RED’s performance to obtain the desired results, scholars usually tune the input parameters, especially the maximum packet dropping probability, into specific value(s). Unfortunately, setting up this parameter into these values leads to good, yet biased, performance results. In this paper, the RED-Exponential Technique (RED_E) is proposed to deal with this issue by dropping arriving packets in an exponential manner without utilizing the maximum packet dropping probability. Simulation tests aiming to contrast E_RED with other Active Queue Management (AQM) methods were conducted using different evaluation performance metrics including mean queue length (mql), throughput (T), average queuing delay (D), overflow packet loss probability (PL), and packet dropping probability (DP). The reported results showed that E_RED offered a marginally higher satisfactory performance with reference to mql and D than that found in common AQM methods in cases of heavy congestion. Moreover, RED_E compares well with the considered AQM methods with reference to the above evaluation performance measures using minimum threshold position (min threshold) at a router buffer.

Random early detection (RED) is widely deployed as a congestion control mechanism in the routers. However, RED is often limited by the difficulty of tuning its parameters under different congestion levels. Adaptive RED (ARED) addresses this problem by adaptively adjusting the aggressiveness of RED settings to keep the average queue size between minimum threshold (minth) and maximum threshold (maxth ). We have observed that the additive increase multiplicative decrease (AIMD) approach used in ARED can always maintain high link utilization but not effective enough in preventing high packet loss rates under heavy congestion. In this paper, we propose an adaptive version of RED which applies non-linear power function instead of linear AIMD approach to achieve better link utilization as well as minimizing the packet loss rates under various traffic load conditions

The congestion control mechanisms used in TCP have been the focus of numerous studies and have undergone a number of enhancements. However, even with these enhancements, TCP connections still experience alarmingly high loss rates, especially during times of congestion. To alleviate this problem, the IETF is considering active queue management mechanisms, such as random early detection (RED), for deployment in the network. In this paper, we first show that the effectiveness of RED depends, to a large extent, on the appropriate parameterization of the RED queue. We then show that there is no single set of RED parameters that work well under different congestion scenarios. In light of this observation, we propose and experiment with more adaptive RED gateways which self-parameterize themselves based on the traffic mix. The results show that traffic cognizant parameterization of RED gateways can effectively reduce packet loss, while maintaining high link utilizations under a range of network loads.

Congestion control in Cluster Wireless Sensor Networks (CWSNs) has drawn widespread attention and research interests. The increasing number of nodes and scale of networks cause more complex congestion control and management. Active Queue Management (AQM) is one of the major congestion control approaches in CWSNs, and Random Early Detection (RED) algorithm is commonly used to achieve high utilization in AQM. However, traditional RED algorithm depends exclusively on source-side control, which is insufficient to maintain efficiency and state stability. Specifically, when congestion occurs, deficiency of feedback will hinder the instability of the system. In this paper, we adopt the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme and propose an improved RED algorithm by using neighbor feedback and scheduling scheme. The congestion control model is presented, which is a linear system with a non-linear feedback, and modeled by Lur’e type system. In the context of delayed Lur’e dynamical network, we adopt the concept of cluster synchronization and show that the congestion controlled system is able to achieve cluster synchronization. Sufficient conditions are derived by applying Lyapunov-Krasovskii functionals. Numerical examples are investigated to validate the effectiveness of the congestion control algorithm and the stability of the network.

Explicit congestion notification (ECN) and active queue management (AQM) Schemes such as random early detection (RED), adaptive random early detection (ARED) and BLUE queues have been proposed for TCP/IP networks to compensate network congestion. However, using ECN requires that ECN be supported by both TCP senders and receivers. This paper presents a novel AQM modification called receiver- window modification (RWM). RWM can be used together with RED, ARED and BLUE queues, to provide congestion avoidance in packet switched networks at ingress and gateway routers. RWM does not require modification to all end system TCP/IP stacks but can be solely implemented in routers. Our RWM scheme helps in reducing the average queue sizes of RED, ARED, BLUE and even ARED-ECN, BLUE-ECN and RED- ECN queues. By reducing the average queue sizes, RWM queues reduce the queuing delay resulting in significant improvements in one-way end-to-end packet delays and dropped packets. It is also shown that the performance of RED- ECN, ARED-ECN and BLUE-ECN queues is heavily dependent on the queues of the downstream routers. RWM modified queues in ingress or gateway routers are not influenced by the number and state of the downstream router as they will piggyback congestion information to the source in the next available acknowledgement packet. We carry out extensive ns2 simulations to show our results and to support our claims.

Active queue management (AQM) algorithm is the key technology of congestion control for routers recommended by IETF. AQM provides a main way to avoid Internet congestion combined with TCP. Random Early Detection (RED), recommended by AQM as the default algorithm for routers of NGN, has become the research hotspot nowadays. In this paper, we proposes an improved RED algorithm named ERED (Enhanced RED) based on the study of existing RED, congestion detection and congestion avoidance. A serial of simulation had been done based on NS2 simulator. The experimental results indicate that the packet loss and stability are better than RED algorithm. The comparison of packet numbers and packet loss numbers under different congestion condition shows that the packet loss and link utilization of ERED are better than RED, which enhances the adaptability of RED algorithm.

Proportional Integral controller Enhanced (PIE) is an Active Queue Management (AQM) mechanism to address the bufferbloat problem. AQM mechanisms tackle bufferbloat by dropping or marking packets before the buffers fill up, but typically do not ensure fairness between responsive and unresponsive flows that share the same bottleneck link i.e., unresponsive flows can starve responsive flows when they co-exist. Recently, there has been an active interest in integrating flow protection mechanisms with AQM mechanisms to collectively tackle the problem of bufferbloat and fairness. There exist two such algorithms: Flow Queue Controlled Delay (FQ-CoDel) and Flow Queue Proportional Integral Controller Enhanced (FQ-PIE) that integrate flow protection with AQM mechanisms. Flow protection is achieved by dividing the incoming flows into separate queues and then applying CoDel/PIE algorithm on respective queues. Although FQ-CoDel is available in the mainline of Linux, there does not exist a model for FQ-PIE. In this paper, we discuss the design and implementation of FQ-PIE in the Linux kernel. We test and evaluate our proposed model of FQ-PIE in different scenarios by comparing the results obtained from it to those obtained for PIE and FQ-CoDel. Besides evaluating the fairness among responsive and unresponsive flows, we also evaluate the fairness among different types of responsive flows, such as when CUBIC TCP shares the same bottleneck link as TCP BBR. We also assess the benefits of integrating flow protection with AQM mechanisms in terms of reducing the latency for thin, latency sensitive flows when they coexist with thick, latency tolerant flows.

The purpose of this research is to design and evaluate a new queue management algorithm effectively controlling the heavy-tailed traffics. Among active queue managements (AQM), Random Early Detection (RED), has been widely used to improve the TCP throughput. The heavy-tailed traffic, however, generates the large fluctuation on the queue causing the degradation of fairness in terms of jitter performance. In this paper, we proposed the Stable time RED (STRED) to improve the jitter and the fairness of jitter performance. STRED enables to stabilize the calculation timing for average queue length leading to suppress the queue fluctuations. We also implemented the STRED mechanism on the ns-2 simulator. In addition, we propose the pseudo model network consisting of multiple input / output buffers. The experiments of different pattern of AQM algorithms were conducted. As the results of simulation, we extracted the following features. Firstly, STRED could sustain the jitter values and large fluctuations of each file size and Pareto distribution. Secondly, STRED at the first incoming buffer made lower and smoother jitter values than the RED method. Thirdly, STRED could improve the fairness of jitter for all file sizes, and especially for heavy-tailed traffics. Finally, STRED creates low jitters and the high fairness in term of jitter meaning that STRED can enhance the quality of mutual communication applications such as Internet telephony.