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用PSO优化基于QoS的WSN路由协议
引用本文:陈璟,张曦煌.用PSO优化基于QoS的WSN路由协议[J].计算机工程与设计,2007,28(20):4931-4933.
作者姓名:陈璟  张曦煌
作者单位:江南大学信息工程学院 江苏无锡214122
摘    要:在过去的10年中,提供服务质量(QoS)保证的路由协议很好的用在了有线网络中,随着无线传感网络(WSN)的广泛使用,就需要考虑如何在无线传感网络中实现QoS的效率.很多QoS度量值都需要被考虑,如数据包时延、带宽效率、能量消耗等.同时QoS也受路由的影响,由于路由解空间随着网络的规模变大而呈指数级的增长,研究路由协议算法的效率就成为一个必然.在研究了智能粒子群最优算法(PSO)后,提出了一个基于PSO的路由算法,不仅考虑了QoS的需求同时也有一个不错的搜索能力.仿真结果表明,与一些典型QoS常规机制比较基于粒子群最优路由算法是有效的.

关 键 词:粒子群算法  无线传感网络  路由协议  服务质量  度量值  仿真环境  优化  路由协议  particle  swarm  optimization  based  wireless  sensor  network  最优  比较  常规机制  仿真结果  搜索能力  需求  路由算法  优算法  粒子群  智能  协议算法  研究  增长  指数  规模
文章编号:1000-7024(2007)20-4931-03
修稿时间:2006-11-07

Routing in wireless sensor network based on QoS with particle swarm optimization
CHEN Jing,ZHANG Xi-huang.Routing in wireless sensor network based on QoS with particle swarm optimization[J].Computer Engineering and Design,2007,28(20):4931-4933.
Authors:CHEN Jing  ZHANG Xi-huang
Affiliation:School of Information Engineering, Southern Yangtze University, Wuxi 214122, China
Abstract:Routing protocols that provide quality of service(QoS) in wired network are well applied for the past ten years.However,as wireless sensor network technology becomes more widely used,how to implement QoS efficiently in the wireless sensor network world need to be investigated.Many QoS metrics should be considered in network design,for example data packet delay,bandwidth efficiency and power consumption.QoS metrics are greatly affected by network routing.It is necessary to research efficient of routing since the routing solution space grows exponentially with the size of the network.After studying intelligent particle swarm optimization(PSO) algorithm,a new routing algorithm based on PSO is described,which has address many QoS metrics together and has an outstanding searching ability.Simulations and comparisons to some typical QoS routine methods show that particle swarm optimization based on rou-ting algorithm is effective.
Keywords:PSO  WSN  routing protocol  QoS  metric  simulation environment
本文献已被 CNKI 维普 万方数据 等数据库收录!
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