大规模带状无线传感器网络QoS路由优化的研究  

Research on QoS Routing Optimization for Wireless Sensor Network with Large-scale Banded Structure

作　　者：张君艳[1] 朱永利[1] 彭伟[1] 

机构地区：[1]华北电力大学控制与计算机工程学院,河北保定071003

出　　处：《电力科学与工程》2010年第4期11-15,共5页Electric Power Science and Engineering

基　　金：国家自然科学基金资助项目(60974125)

摘　　要：针对输电线路监测系统对无线传感器网络实时性和可靠性要求较高的特点,抽象出大规模带状无线传感器网络QoS路由模型,把网络带宽、时延、跳数、包成功接收率作为链路约束。鉴于蚁群算法收敛速度过慢、易陷入局部最优解和遗传算法不能充分利用系统反馈信息的缺陷,提出了一种用遗传—蚁群算法寻求最优QoS路径的方法。仿真结果表明,改进的算法在遗传算法生成初始信息素分布的基础上利用蚁群算法能够快速地找到满足约束的最优路径,网络规模越大其优势越明显,有效地解决了大规模带状无线传感器网络QoS路由优化的问题。Recent developments in the field of transmission line monitoring system have led to a renewed interest in wireless sensor network（WSN）, which is characterized by the real time and reliability. However, there are increasing concerns that genetic algorithm and ant colony algorithm are being disadvantaged because of the issue of local optimality, so this paper focused on a new method of the combination of genetic algorithm and ant colony algorithm （GAAA） to solve the problem of optimal path which was verified by the simulation. In order to seek the optimal path for data transmission in wireless sensor network, the network bandwidth, delay, hop count and packet reception rate were considered as link constraints in the abstract model of wireless sensor network with large-scale banded structure. The results show that the optimal QoS path can be quickly found via ant colony algorithm, which is based on the initial pheromone distribution generated by genetic algorithm. The GAAA algorithm can effectively solve the QoS routing optimization problem of wireless sensor network with large-banded structure.

关 键 词：无线传感器网络 遗传算法 蚁群算法 服务质量 输电线路监测 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]