协作MIMO无线传感器网络中多目标进化算法分析  

Multi-objective Evolutionary Optimizations of Wireless Sensor Network Based on Cooperative MIMO

作　　者：荣伟[1] 裴廷睿[1] 李哲涛[1] 申瑞珉[1] 

机构地区：[1]湘潭大学信息工程学院,湖南湘潭411105

出　　处：《小型微型计算机系统》2013年第2期258-263,共6页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(61070180)资助;湖南省科技厅项目(2011GK3200)资助;湖南省高校创新平台开放基金项目(2009GK3016)资助

摘　　要：现有的基于协作MIMO的无线传感器网络(WSN)传输策略设计往往只注重节能方面,追求网络生存时间的最大化,而忽略了网络数据速率在大部分实际工程应用中的重要性.基于线性多跳协作MIMO传输模型,分析了该模型的数据速率、平均功耗及生存时间并提出基于多目标进化算法——NSGA-Ⅱ的WSN优化算法.在NSGA-Ⅱ中,通过对种群进行初始化,利用二元锦标赛法选择,单点交叉,动态变异等操作进行进化,并采取利用最小生成树的权值表示拥挤度的方法保证种群的分布性.仿真结果表明:相比于聚集函数法,NSGA-Ⅱ所获得的网络生存时间更长.更重要的是,仿真给出一些能达到网络数据速率与生存时间两者同时最大且使网络功耗处于较小水平的参数值,能有效地指导于WSN工程应用.Existing cooperative MIMO-based transmission strategies for wireless sensor networks（WSN}, pay too much attention on how to save energy and how to increase the lifetime. However,the data rate isn＇t considered almostly. In this paper,the data rate, the power and the lifetime of network are analyzed firstly, and then we propose a multi-objective evolution algorithm based on those ob- jectives. In NSGA- Ⅱ, we select the population by using the binary tournament firstly, then using single point selection and dynamic mutation rate to evolve the population. At last, for the purpose of the best distribution of the population, we use the Minimum Span- ning Tree （MST） algorithm. The simulation results show that our algorithm is better than aggregating functions on the network life- time, and also give some parameter values that can reach good balance between the three objectives. Moreover, the results can give an effective guidance for engineering applications.

关 键 词：无线传感器网络 协作MIMO技术 NSGA-Ⅱ 网络数据速率 网络生存时间 网络平均功耗 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]