Research Of Congestion Control Mechanism Based On Active Queue Management And Stabilities

Network congestion control mechanism plays a key role in maintaining network stability and guaranteeing quality of service. There are two kinds of congestion control, one is end hosts based (TCP) and the other is intermediate router based (AQM). The AQM has advantages in the enhancement of the efficiency of transfers, network congestion preventing and mitigating, the link utilization improvement, and the packet loss rate reduction, etc. But many researchers find that AQM algorithm is very sensitive to network-load variations, which include burst network traffic, delay jitter and bandwidth limitation, and mixed type traffic. Thus, how to avoid network congestion, increase network traffic performance, and optimize the configuration of network resources to ensure network reliability, timeliness, stability, robustness, arouse the academia and industry’s extensive attention.This thesis focuses on the following topics. First, the platform of AQM based on NS2 is made up. In order to induce the influence factor of the performance of AQM, a series of typical AQM are analysed and compared through this platform. Then, based on the above conclusions, three different types of AQM are proposed. Finally, from the perspective of nonlinear theory, using the packet loss probability gain instead of the complex control function of AQM algorithm, the stability and dynamic behavior of congestion control system is analyzed with the network delay? .The main contributions of the work are as follows:1. There has not existed a universal AQM designing and testing frame yet. A designing and testing platform for AQM algorithm based on Network Simulator 2 is introduced. The platform is divided into the following four parts: The AQM algorithm engine module; the algorithm performance analysis module; network topology module and traffic burst module. Seeking to cover all the contingencies of network congestion, the universal test scenarios are designed for AQM testing based on previous experience. Following an exhaustive simulation evaluation through this testing platform, we test and verify the performance of many AQM. The result shows that the network parameters ( N , RTT ,C ), the short-time Web traffic, the non-response UDP traffic, the congestion detection method and the queue control function of AQM, are all effecting the performance of congestion control system.2. We present a self-tune AQM algorithm with acceleration factor by analyzing Blue algorithm and its variants, which is called SABlue (Self-tune Accelerate Blue). In order to make the queue length keep in the aim area, this algorithm adopts instantaneous queue length as the parameter of incipient congestion detection and calculates the step size of packet drop probability by using load factor. Furthermore, for the sake of response speed, we lead in the acceleration factor in alert area when the network traffic is changed suddenly. Parameter ? can affect the stability of the queue and response rate of burst stream, taking into account the performance trade-offs of the link utilization and packet loss ratio, we choose ? between 1.4 and 3.7. Finally, the simulation demonstrates that SABlue algorithm is more robust, carrying lower packet loss and shorter convergence time in the situation of dynamic traffic. The combination property of SABlue is more excellent than other AQM algorithms.3. In order that the AQM algorithm has smooth control effect, especially in the dynamic network, an adaptive Fuzzy-Logic algorithm with active-flow-Number estimation (called NFL) is poposed. It is composed of two main parts: the fuzzy AQM and the active-flow estimation strategy. Taken the tradeoff among the queue performance, link utilization and other indicators, a set of fuzzy rule is built for NFL to adapt to the dynamic network situation. Furthermore, an optimization mothed is raised, which reduces the computational complexity of fuzzy AQM. A stateless active-flow estimation strategy baesd on Bloom Filter is introduced to capture network congestion status. In order to make up for the deficiency of fixed fuzzy rules, which leads fuzzy AQM robustless, an output gain compensator for fuzzy AQM in accordance with active-flow-number parameter is proposed. Simulation results demonstrate that NFL is adpatvie to dynamic network, while having fast convergence rate and stable steady-state queue control performance. The comprehensive performance of NFL is more excellent than other AQM algorithms.4. In order to solve the fair resources competition issues for TCP flows and UDP flows, an RMVQ(Rate-perceptive Multi Virtual Queue) algorithm is introduced. We use the instantaneous queue length as the primary means, and apply the active flow perceive module as the supplementary means. The active flows perceive module collects flows’information online, and calculates the number of activity UDP, the rate of UDP, and the number of activity TCP periodicly. According to load information, virtual queue distribution module divides buffsize into two parts. One for UDP, anothor is for TCP. The idea of differentiated services is introduced to design the two queue strategies. Simulation results show that, in the UDP/TCP mixed flow scenarios, RMVQ algorithm can catch UDP load trends, and allocate virtual queue accurately. Compared with the other AQMs, the comprehensive performance of RMVQ is satisfactory.5. The uncertain communication delay can cause network congestion control system performance degradation, and even instability. Stability of the equilibrium solution of GAIMD/AQM (Generalized Additive Increase Multiplicative Decrease/Active Queue Management) system is investigated based on analyzing the corresponding transcendental characteristic equation. Using the delay as the bifurcation parameter, we demonstrate that when the delay crosses a critical value, Hopf bifurcation occurs and a periodic solution generates from the equilibrium point. Then, the bifurcation direction and stability of periodic solution is analyzed by means of the center manifold theorem and the normal form theory. Moreover, the impact of the parameters configuration on the performance of the GAIMD/AQM system is investigated exhaustively. Finally, numerical simulations are carried out to verify the feasibility of the theoretical results. The results show that there is a key value of the bifurcation ? 0 for the system. This is consistent with the theoretical results.