基于改进量子粒子群和主动PI模型的自适应无线传感器网络拥塞控制算法设计

Design of Wireless Sensor Network Congestion Control Algorithm Based on Active PI Model and Improved Quantum Particle Swarm Optimizing Algorithm

摘要:

针对无线传感器网络中路由节点需要转发大量数据导致网络拥塞,从而引起节点丢包率高和网络吞吐率过低的问题,提出了一种基于主动PI模型和改进量子粒子群优化算法的拥塞控制方法；首先定义了丢包率和队列长度计算方式；设计了改进的PI主动队列管理模型,然后,为了改进PI模型的控制效果,采用改进的量子粒子群算法对PI主动队列管理模型中的比例系数和积分系数kP和kI进行参数优化,从而得到能实现WSN自适应控制的主动PI控制模型；最后,对基于量子粒子群算法和PI主动队列模型的网络拥塞算法进行了描述和说明；仿真实验表明:文中提出的拥戴控制方法能有效实现WSN拥塞控制,是一种适用于WSN的有效拥塞控制方法,与其它方法相比,具有较短的平均队列长度和较大的网络吞吐率,具有很强的可行性。

Abstract:

Aiming at the route node in the wireless sensor network having to transferring amount of data leading to the network congestion, then resulting to the high node packet dropping rate and low network throughput rate, a WSN network congestion control method based on active PI model and improved quantum particle swarm algorism optimizing algorithm is proposed. Firstly, the node packet dropping rate and queue length are defined, the improved PI active model is designed, then in order to improve the effect of PI model, the improved quantum particle swarm algorithm is used to optimize the parameter of proportionality and integration is optimized, therefore, the active PI control model is obtained to realize the WSN adaptive control. Finally, the network congestion algorithm based on quantum particle swarm algorithm and PI active model is described. The simulation experiment shows the network congestion control method in this paper can realize the WSN congestion control. It is a suitable method for network congestion, compared with other methods, it has short average queue length and high network throughput rate with stronger feasibility.