In this letter, we propose an improved Droptail algorithm that introduces the random packet drop strategy. Our theoretical analysis and experiments prove that the improved Droptail can match the most performance of AQM algorithms in stabilizing the TCP system and solving the global synchronization problem, while significantly reducing the complexity of the router control. This fact shows that our algorithm is superior to the most popular AQM algorithms such as RED, PI, etc.

We propose a scheduling method called SCQ (Smoothly Changing Queue) which can control service rate by bulk size of video streaming services such as IPTV and VoD. Since SCQ allows queue length to change smoothly, video streaming services can be stably provided with low jitter. Queueing analysis results show that SCQ can more stably deliver video streaming with low jitter and loss than existing AQMs or queue length-based rate control methods.

Service differentiation is one of the key issues in the current Internet. In this paper, we focus on a recent proposal for proportional loss rate differentiation which employs a single FIFO queue, an AQM algorithm for computing the packet drop probability, and a counter-based packet dropping routine for achieving the intended proportional loss rate differentiation among classes. It is first shown that, when the target dropping probability of a class is large, the counter-based packet dropping routine may yield a significant amount of error between the target and measured drop probabilities for the class, and subsequently, fails to maintain the loss rate ratios between classes as intended. To avoid this problem, a new compensatory packet dropping routine is developed in this paper. Then, a series of simulation experiments are conducted using the ns-2 simulator to assess the performances of the two dropping routines under various congestion conditions and quality spacings between classes. The simulation results show that, unlike the counter-based dropping routine, the proposed compensatory dropping routine is effective in keeping the loss rate ratios between classes closely on target regardless of the degree of congestion and quality spacing between classes, while the two dropping routines perform similarly in terms of throughput and queueing delay in the bottleneck link. In addition, such robustness of the proposed routine is achieved without any additional control parameter or computational effort compared to the counter-based routine.

Active Queue Management (AQM) based on nonlinear difference equations is proposed to solve the end-to-end TCP network congestion problem. The proposed AQM scheme can guarantee the stability of the multiple bottleneck network by nonlinear control of dropping probability of the routers by imposing some restrictions on the AQM parameter. Nonlinear control often relies on some heuristics and network traffic controllers that appear to be highly correlated with the multiple bottleneck network status. Based on the proposed nonlinear difference equations for TCP flows control across the network, this paper reveals the reasons of congestion of multiple bottleneck AQM, and provides a theorem for avoiding network congestion. Moreover, we give simulations to verify the results for nonlinear control of the multiple bottleneck network congestion.

In this letter, we propose a protocol sensitive random early detection algorithm for active queue management to improve fairness between TCP and UDP flows and to reduce delay time with small overheads. The algorithm classifies the packets into responsive and unresponsive flows, and applies the RED algorithm individually to each classified group. Using ns-2 simulations, we showed the effectiveness of the proposed PSRED algorithm compared with several well-known AQM schemes, such as RED and RED-PD algorithms.

The window flow control based end-to-end TCP congestion control may cause unfair resource allocation among multiple TCP connections with different RTTs (round trip times) at a bottleneck link. In this paper, in order to improve this unfairness, we propose the active ECN which is an ECN based active queue mechanism (AQM). A bottleneck router with the proposed mechanism marks TCP segments with a probability which depends on the RTT of each connection. By enabling the TCP senders to reduce their transmission rate when their packets are marked, the proposed mechanism can realize the same transmission rate among TCP connections with different RTTs. Furthermore, the active ECN can directly mark ACKs from TCP receivers, while the conventional ECN marks TCP segments coming from the TCP senders. As a result, the queue length distribution at the bottleneck link gets stabilized, because the sender can quickly react to the marking according to variation of the queue length.

Using the Proportional Integral Derivative (PID) principle of classical feedback control theory, this paper develops two general congestion control algorithms for routers implementing Active Queue Management (AQM) while supporting TCP/IP traffic flows. The general designs of non-interacting (N-PID) and interacting (I-PID) congestion control algorithms are tailored for practical network scenarios using the Ziegler-Nichols guidelines for tuning such controllers. Discrete event simulations using ns are performed to evaluate the performance of an existing F-PID and new N-PID and I-PID algorithms. The performance of N-PID and I-PID is compared mutually as well as with the F-PID algorithm. It reveals that N-PID and I-PID have higher speed of response but lower stability margins than F-PID. In general the accurate following of the target queue size by the PID principle congestion control algorithms, while providing high link utilization, low loss rate and low queuing delays, is also demonstrated.

In this letter, we evaluate the performance of several adaptive and non-adaptive AQM schemes for congestion control in a dynamic network environment with variable bandwidth links. The AQM schemes examined are RED, BLUE, Adaptive RED, REM, AVQ and PI controller. We compare their queueing performance and show that none of them can derive stable queue length and low packet drop rate simultaneously in networks where both input traffic and available output bandwidth are time varying. Adaptive and efficient algorithms should be designed and applied in order to improve the adaptiveness and robustness of congestion control in dynamic networks such as Internet.

In this paper, we propose a nonlinear control model to characterize the AQM algorithm-GREEN. Based on this model, we analyze its performance and prove that there exists a stable oscillation when in equilibrium. Furthermore, we also investigate the effects of the factors such as bandwidth, round trip time, and load level on the amplitude and frequency of the oscillation. Theoretical analysis and simulation results indicate that GREEN algorithm is insensitive to the network conditions when the link rate and the round trip time are relatively small and becomes more sensitive to the change of network conditions when the bandwidth delay product is relatively high. For GREEN the adaptability to a wide range of network conditions is based on the compromising of the efficiency.

Evolutionary learning methods have been applied to a variety of different problems. In this paper, a new algorithm for active queue management based on an evolutionary learning model is proposed. This novel algorithm generates packet marks for the purpose of improving robustness and responsiveness of congestion control in the Internet routers, while maintaining a reasonable degree of queueing performance such as utilization, delay, and packet drops due to buffer overflow. Simulation results demonstrate the effectiveness of the proposed algorithm and compare the performance of various algorithms.

As an enhancement mechanism for the end-to-end congestion control, AQM (Active Queue Management) can keep smaller queuing delay and higher throughput by purposefully dropping the packets at the intermediate nodes. Comparing with RED algorithm, although the PI (Proportional-Integral) controller for AQM designed by C. Hollot improves the stability, it seems unscientific to tune the controller parameters through trial-error, moreover the transient performance of the PI controller is not perfect, such as the regulating time is too long. In order to overcome this drawback, in this paper, the PID (Proportional-Integral-Differential) controller is proposed to speed up the responsiveness of AQM system. The controller parameters are tuned based on the determined gain and phase margins. The simulation results show that the integrated performance of the PID controller is obviously superior to that of the PI controller.