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    基于网络状态参数估计的主动队列管理PI改进算法

    An Improved PI Active Queue Management Algorithm Based on Network State Parameters Estimation

    • 摘要: 作为一种重要的主动队列管理手段,PI控制器算法通过积分器的引入有效地消除了队列长度控制的稳态误差,在提高网络吞吐的同时缩短了排队时延.但是PI控制器不能根据网络状态变化而自动调整控制参数,故当网络流量变化时PI控制器的收敛速度很慢.基于TCP-AQM系统模型,对经过中间节点的活动连接数、平均往返时间和前向链路容量等3个参数进行估计.通过计算击中概率的倒数,估计出活动流数;通过计算单位时间的数据包数,估计出网络容量;通过往返时延、活动流数、网络容量以及丢包概率在稳态时的关系式,估算出平均往返时延.在此基础上,提出了对网络状态变化自适应调整控制参数改进的快速收敛PI算法——FCPI算法.仿真结果表明,该算法有效提高了算法的收敛速度,并且鲁棒性好,易于实现,适用于未来高速网络的路由器.

       

      Abstract: As an important active queue management scheme, PI controller eliminates the steady state error of queue length with the introduction of integral factor, improving throughput while reducing queuing delay. But it can not adapt its control parameters when network state varies with time. So when traffic flows change, the PI controller can not converge quickly with the traffic flows. Based on the thoughts of detecting and estimating network state information through the network flows, the amount of active flows, average round trip time (RTT) and capacity of outgoing link are estimated. The amount of active flows is estimated by calculating the inverse proportion of hit function probability. The network capacity is estimated by average data packets per unit time. The average RTT is estimated by the relation equation of the amount of active flows, network capacity and data packets loss probability in the steady state. A new scheme called fast convergent PI (FCPI) is proposed based on TCP-AQM system model and the network state parameters estimation, in which the controller can be adjusted according to the real-time network state. Simulation results show that the new scheme not only improves the convergent rate of PI controller, but also appears to be robust and effective in different scenarios, which makes it more suitable for high speed routers.

       

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