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改进神经元PID无线拥塞研究
Research on improved neural network PID congestion control in ad hoc network
【摘要】 神经元PID算法能较好地控制瓶颈节点的队列长度,但当网络环境发生较大变化时,其控制效果往往难以保证。根据Ad Hoc网络环境参量时变的特点,推导了无线TCP/AQM离散模型,在神经元算法的加权系数中引入二次型性能指标。另外神经元增益K是系统敏感参数,而恒定的K值不易适应时变的无线自组织网络,据此设计了一种改进二次型性能指标神经元PID的AQM。仿真结果表明:在动态拓扑、突发流及链路容量变化的Ad Hoc网络中,该改进算法优于PI算法。
【Abstract】 Neuron PID can regulate the queue size of a bottleneck node successfully,but its control effect is worse when the network state changes.For ad hoc network’s time-varyingi,t deduces discrete math model of TCP/AQM control object in wireless network.It introduces quadratic performance index to weighting coefficient modification for neuron PID controller.Fur-thermore neuron gain K is system sensitive coefficient.So constant K cant’ be fit for time-varying ad hoc network.Finally,a new improved quadratic performance index neuron PID AQM is proposed.Matlab and NS-2 simulations demonstrate that the performance of new algorithm is better than PI under different link capacity,dynamical topology and sudden flow condition.
【Key words】 ad hoc network; congestion control; quadratic performance indexi; mproved neuron PID;
- 【文献出处】 计算机工程与应用 ,Computer Engineering and Applications , 编辑部邮箱 ,2010年35期
- 【分类号】TP393.06
- 【被引频次】2
- 【下载频次】72