Research On TCP Congestion Control In Ad Hoc Network

Ad Hoc network is a multi-hop, temporary and self-configuring network of mobile devices with wireless receive-send equipment. Each node acts either as a host generating flows, being the destination of flows from other mobile nodes, or as a router forwarding flows directed to other nodes. Its features of multi-hop, one against many communication method and wireless link quality will lead to network local and global congestion. Ad Hoc network bandwidth resource is very limited, so congestion control research is very important.In this dissertation, an emphasis research has been made on the Ad Hoc network TCP congestion control from congestion control source algorithm and link algorithm. This paper first analyzes the stability and robustness of PI (Proportional Integral) AQM (Active Queue Management) and PID (Proportional Integral Differential) AQM in Ad Hoc network. Secondly, it deduces the TCP/AQM differential model. Thirdly, it designs an adaptive neuron PID AQM controller based on proportional summation differential (PSD). Finally, it models the TCP performance in Ad Hoc network based on congestion control principle. The main research content is as follows:(1) Stability of PID AQM algorithm is base of congestion control. Now PID design and tuning often use experience and experimentation. These methods lack theoretic analysis of stability region and often get some isolated tuning results. Stability characterization of PID scheme is analyzed in wireless and delay Ad Hoc network. Finally, it gives stability regions of PID-AQM control under different differential coefficients in delay networks. Comparing with tradition engineering tuning ways, the research also gives stability theory of PID in delay system and helps to determinate controller coefficients. Matlab and NS (Network Simulator) simulations indicate that stability regions and its advantage are proved.(2) The object model which researchers deduce is not accurate expression of the real physical system. Robust control goal is to maintain system stability and performance when a controlled object changes its parameters or modeling is inaccurate. Robustness of the PI AQM algorithm is important performance target. Now PI AQM often uses experience and experimentation to design controller and its algorithm. As controlled object, Ad Hoc network parameters often change. So how far can the controller coefficients maintain system stability? This research lacks theoretic analysis of robustness. According to robustness control theory, it analyzes robustness characterization of PI algorithm in delay Ad Hoc network. It deduces the relation of link capacity, number of TCP connection and delay for certain PI controller. Finally, it gives range of the delay under the PI controller's parameters. By Matlab and NS simulations, the range of delay parameter robustness is proved.(3) The research on AQM is usually concerned about queue controller design. As a controlled object, transmission control protocol (TCP) is often realized by Network Simulator (NS) simulation. So it is necessary to study the character of TCP and AQM in Ad Hoc network because the relation between TCP and AQM in Ad Hoc network is not clear. TCP windows size and queue length differential equations are deduced based on TCP window additive-increase multiplicative-decrease rule and queuing principle. Then, congestion loss probability differential equation is deduced based on proportional integral AQM control. So the Ad Hoc network TCP/AQM differential model is proposed through building the simultaneous differential equations. The comparison simulations show that the new model can estimate Ad Hoc network performance well. The model research also shows that the number of hops, wireless loss and very small queue become AQM performance bottlenecks. Furthermore, the queue information can help TCP discriminate between congestion loss and wireless loss in Ad Hoc network.(4) Neuron PID algorithm can control queue length successfully in many AQM scheme, but its neuron gain is sensitive for controlled object state. So it is difficult to guarantee the control performance because of the fixed neuron gain in neuron PID algorithm. Congestion window size, loss probability and queue length differential equations are deduced based on TCP window additive-increase and multiplicative-decrease (AIMD) principle and AQM mechanism. TCP/AQM control system model is obtained in Ad Hoc network through the small perturbations and equations linearization. Then it introduces recursion and modification gain to neuron PID based on the model. Finally, a neuron adaptive proportional summation differential (PSD) AQM scheme is proposed. PSD algorithm can modify neuron gain dynamically according to the network situation. NS simulations demonstrate that PSD queue management performance is better than neuron PID under conditions of wireless packet loss, sudden flow and different link capacity.(5) The Reno wired throughput model proposed by Padhye can not estimate accurately Ad Hoc network throughput because Ad Hoc network has characteristics of multi-hop and wireless channel. But Ad Hoc network TCP performance modeling use Markov chain usually. Based on 802.11 protocol DCF (Distributed Coordination Function) RTS/CTS (Request To Send/ Clear To Send) communication mechanism, multi-hop topology available link capacity is deduced. Then TCP windows size, available link capacity and wireless packet loss probability mathematical relation is deduced based on congestion window principle of TCP-Reno version and TCP-Tahoe version. Therefore Ad Hoc network TCP-Tahoe model and TCP-Reno model were proposed. The simulation research shows that the new TCP models can estimate Ad Hoc network TCP window size and throughput. The models average error is below 7%. Reno's fast-recovery can not correct all packets in correlated loss and leads to time-out retransmit at last. So Reno performance is worse than Tahoe in Ad Hoc network.