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基于二次型优化的神经元PID无线拥塞算法研究
PID congestion control based on neural network 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,设计了一种基于二次型性能指标的神经元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 often is worse when the network state changes.For Ad Hoc network’s time-varying,it deduced discrete math model of TCP/AQM control object in wireless network.It introduced Quadratic Performance Index to weighting coefficient modification for neuron PID controller.Finally,a neuron Proportional-Integral-Differential AQM based on Quadratic Performance Index is proposed.Matlab and NS-2 simulations demonstrate that new algorithm performance is better than PI under different link capacity,dynamical topology and sudden flow condition.
【Key words】 Ad Hoc network; congestion control; quadratic performance index; neuron PID;
- 【文献出处】 苏州大学学报(自然科学版) ,Journal of Suzhou University(Natural Science Edition) , 编辑部邮箱 ,2009年03期
- 【分类号】TN92
- 【被引频次】4
- 【下载频次】84