期刊导航

论文摘要

基于组合优化理论的能量感知路由算法

Energy aware routing algorithm based on combination optimization theory

作者:李巍(兰州职业技术学院网络信息中心);赵璇(兰州职业技术学院网络信息中心);温畈(兰州职业技术学院网络信息中心);余隋怀(西北工业大学机电学院);田少辉(中国人民解放军总后勤部建筑工程研究所)

Author:LI Wei(Network Information Center, Lanzhou Vocational Technology Colleg);ZHAO Xuan(College of Electronics and Information Engineering, Sichuan University);WEN Fan(College of Electronics and Information Engineering, Sichuan University);YU Sui Huai(School of Mechanical Engineering, Northwestern Polytechnical University);TIAN Shao Hui(Chinese People's Liberation Army Construction Engineering Research Institute)

收稿日期:2014-10-31          年卷(期)页码:2015,52(6):1272-1276

期刊名称:四川大学学报: 自然科学版

Journal Name:Journal of Sichuan University (Natural Science Edition)

关键字:移动自组织网络; OLSR路由算法; 自回归差分滑动平均; 最小二乘支持向量机

Key words:.Mobile Ad hoc Network;OLSR routing algorithm; Auto regressive integrated moving average; Least squares Support vector machine

基金项目:国家高技术研究发展计划(2009AA093303)

中文摘要

针对传统OLSR算法的传输功率消耗和节点剩余能量之间的矛盾,提出了一种基于组合优化理论的能量感知路由算法(EW OLSR).首先根据传输功率消耗和节点剩余能量构建节点能量消耗数学模型,并将其作为路由选择目标函数,然后在节点剩余能量计算中引入ARIMA LSSVM组合预测模型,最后根据能量消耗最小路径选择数据传输路由.实验结果表明,EW OLSR算法不仅减少了网络能量消耗和传输时延,而且提高了分组到达率,在无线网络中具有广阔的应用前景.

英文摘要

According to the contradiction between the transmission power consumption and node residual energy in OLSR algorithm, this paper propose an energy aware routing algorithm based on combination optimization theory (EW OLSR). Firstly, the mathematical model of node energy cost is constructed according to the transmission power consumption and node residual energy, and make it as the routing objective function, and secondly, ARIMA LSSVM combination forecast model is introduced in the calculating remaining power node, and finally according to the energy minimum cost route is chosen as data transmission route. The simulation results show that, the proposed algorithm not only reduces the network energy cost and transmission delay, but also improves the packet arrival rate, and has wide application prospect in the wireless network

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