Congestion-Aware Scalable Video Streaming

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Design and performance evaluation of a state-space based AQM

Recent research has shown the link between congestion control in communication networks and feedback control system. In this paper, the design of an active queue management (AQM) which can be viewed as a controller, is considered. Based on a state space representation of a linearized fluid flow model of TCP, the AQM design is converted to a state feedback synthesis problem for time delay systems. Finally, an example extracted from the literature and simulations via a network simulator NS (under cross traffic conditions) support our study

Simulation Model of Enhancing Performance of TCP/AQM Networks by Using Matlab

Internet networks are becoming more crowded every day due to the rapid development of modern life, which causes an increase in the demand for data circulating on the Internet. This creates several problems, such as buffer overflow of intermediate routers, and packet loss and time delay in packet delivery. The solution to these problems is to use a TCP/AQM system. The simulation results showed that there were differences in performance between the different controllers used. The proposed methods were simulated along with the required conditions in nonlinear systems to determine the best performance. It was found that the use of optimization Department of Electro-mechanical Engineering, University of Technology - Iraq tools (GA, FL) with a controller could achieve the best performance. The simulation results demonstrated the ability of the proposed methods to control the behavior of the system. The controller systems were simulated using Matlab/Simulink. The simulation results showed that the performance was better with the use of GA-PIDC compared to both FL-PIDC and PIDC in terms of stability time, height, and overrun ratio for a network with a variable queue that was targeted for comparison. The results were: the bypass ratio was 0, 3.3 and 21.8 the settling time was 0.002, 0.055, and 0.135; and the rise time was 0.001, 0.004 and 0.008 for GA-PIDC, FL-PIDC and PIDC, respectively. These results made it possible to compare the three control techniques

Simulation Model of Enhancing Performance of TCP/AQM Networks by Using Matlab

Internet networks are becoming more crowded every day due to the rapid development of modern life, which causes an increase in the demand for data circulating on the Internet. This creates several problems, such as buffer overflow of intermediate routers, and packet loss and time delay in packet delivery. The solution to these problems is to use a TCP/AQM system. The simulation results showed that there were differences in performance between the different controllers used. The proposed methods were simulated along with the required conditions in nonlinear systems to determine the best performance. It was found that the use of optimization Department of Electro-mechanical Engineering, University of Technology - Iraq tools (GA, FL) with a controller could achieve the best performance. The simulation results demonstrated the ability of the proposed methods to control the behavior of the system. The controller systems were simulated using Matlab/Simulink. The simulation results showed that the performance was better with the use of GA-PIDC compared to both FL-PIDC and PIDC in terms of stability time, height, and overrun ratio for a network with a variable queue that was targeted for comparison. The results were: the bypass ratio was 0, 3.3 and 21.8 the settling time was 0.002, 0.055, and 0.135; and the rise time was 0.001, 0.004 and 0.008 for GA-PIDC, FL-PIDC and PIDC, respectively. These results made it possible to compare the three control techniques

Design of Network Traffic Congestion Controller with PI AQM Based on ITAE Index

Establishing the proper values of controller parameters is the most important thing to design in active queue management (AQM) for achieving excellent performance in handling network congestion. For example, the first well known AQM, the random early detection (RED) method, has a lack of proper parameter values to perform under most the network conditions. This paper applies a Nelder-Mead simplex method based on the integral of time-weighted absolute error (ITAE) for a proportional integral (PI) controller using active queue management (AQM). A TCP flow and PI AQM system were analyzed with a control theory approach. A numerical optimization algorithm based on the ITAE index was run with Matlab/Simulink tools to find the controller parameters with PI tuned by Hollot (PI) as initial parameter input. Compared with PI and PI tuned by Ustebay (PIU) via experimental simulation in Network Simulator Version 2 (NS2) in five scenario network conditions, our proposed method was more robust. It provided stable performance to handle congestion in a dynamic network

Adaptive Active Queue Management based on Queue Ratio of Set-point Weighting

Presently, active queue management (AQM) is one of the important considerations in communication networks. The challenge is to make it simple and robust in bursty traffic and uncertain network conditions. This paper proposes a new AQM scheme, an adaptive ratio proportional integral (ARPI), for adaptively controlling network congestion in dynamic network traffic conditions. First, AQM was designed by adding a set-point weighting structure to a proportional integral (PI) controller to reduce the burstiness of network traffic. Second, an adaptive set-point weighting based on the ratio of instantaneous queue length to the set-point queue and the buffer size was proposed to improve the robustness of a non-linear network. The proposed design integrates the aforementioned expectations into one function and needs only one parameter change to adapt to fluctuating network condition. Hence, this scheme provides lightweight computation and simple software and hardware implementation. This approach was analyzed and compared with the PI AQM scheme. Evaluation results demonstrated that our proposed AQM can regulate queue length with a fast response, good stability under any traffic conditions, and small queuing delay

Simulation model of ACO, FLC and PID controller for TCP/AQM wireless networks by using MATLAB/Simulink

The current work aims to develop a suitable design for control systems as part of a queue management system using the transmission control protocol/and active queue management (TCP/AQM) protocol to handle the expected congestion in the network. The research also aims to make a comparison between the different control methods, including the traditional proportional integral derivative (PID) and the expert fuzzy logic control (FLC), as well as the optimal ant colony optimization (ACO) that is used according to the performance improvement criteria to reach the best values for parameters the traditional controller (kd, ki, k p), where the addition of the performance indicator time-weighted absolute error (ITAE) was adopted. The use of this method without any other optimization algorithm that can be applied to adjust the parameters of the PID to verify the possibility of improving performance and enhance that with experience and to know the level of improvement for this particular system being the subject of the study. The results showed the superiority of the optimal ACO over both the FLC expert and the conventional PID, as well as the superiority of the FLC expert over the traditional PID

Proportional-integral genetic algorithm controller for stability of TCP network

The life development and increase the number of internet users imposed an increase in data circulating on the internet network and then make the network more congestion. As a result of all this, some problems arose such as time delay in packets delivery, loss of packets, and exceed the buffer capacity for the middle routers. To overcome those problems, transmission control protocol and active queue management (TCP/AQM) have been used. AQM is the main approach used to control congestion and overcome those problems to improve network performance. This work proposes to use the proportional-integral (PI) controller with a genetic algorithm (GA) as an active queue manager for routers of the Internet. The simulation results show a good performance for managing the congestion with using proportional-integral genetic algorithm (GA-PI) controller better than the PI controller

A hardware scheduler based on task queues for FPGA-based embedded real-time systems

A hardware scheduler is developed to improve real-time performance of soft-core processor based computing systems. A hardware scheduler typically accelerates system performance at the cost of increased hardware resources, inflexibility and integration difficulty. However, the reprogrammability of FPGA-based systems removes the problems of inflexibility and integration difficulty. This paper introduces a new task-queue architecture to better support practical task controls and maintain good resource scaling. The scheduler can be configured to support various algorithms such as time sliced priority scheduling, Earliest Deadline First and Least Slack Time. The hardware scheduler reduces scheduling overhead by more than 1,000 clock cycles and raises the system utilization bound by a maximum 19.2 percent. Scheduling jitter is reduced from hundreds of clock cycles in software to just two or three cycles for most operations. The additional resource cost is no more than 17 percent of a typical softcore system for a small scale embedded application

Quadratic exponential random early detection: a new enhanced random early detection-oriented congestion control algorithm for routers

Network congestion is still a problem on the internet. The random early detection (RED) algorithm being the most notable and widely implemented congestion algorithm in routers faces the problems of queue instability and large delay arising from the presence of an ineffectual singular linear packet dropping function. This research article presents a refinement to RED, named quadratic exponential random early detection (QERED) algorithm, which exploits the advantages of two drop functions, namely quadratic and exponential in order to enhance the performance of RED algorithm. ns-3 simulation studies using various traffic load conditions to assess and benchmark the effectiveness of QERED with two improved variants of RED affirmed that QERED offers a better performance in terms of average queue size and delay metrics at various network scenarios. Fortunately, to replace/upgrade the implementation for RED algorithm with QERED’s in routers will require minimal effort due to the fact that nothing more besides the packet dropping probability profile got to be adjusted