摘要
为了最大化网络数据收集同时均衡节点能量消耗,研究一类基于分簇的无线传感器网络的移动数据收集方案;其中节点的数据产生速率是变化的,将最大化网络数据收集量建模为一个非线性优化问题,通过对偶分解,分层优化以及梯度下降法获得最优的数据产生速率、链路速率以及汇聚节点停驻时间分配方案。仿真结果表明所提方法在均衡网络能耗和最大化数据收集量方面具有良好的性能。
To maximize the amount of data gathering and balance the energy consumption of the nodes, a scheme of mobile data gathering in cluster based wireless sensor networks (WSNs) is considered,where the data rates of the nodes are adjustable. The problem of maximizing the data gatliering is formulated as a nonlinear programming, the methods of dual decomposition,layered optimization and sub-gradient descent are employed to derive the optimal allocations of data rates,flow rates and the sojourn time of the mobile sink. demonstrate that the method proposed can obtain a better performance in balancing the energy consumption and maximizing the amount of data gathering.
作者
韩宗源
吕晓军
贾新春
王小书
白伟
HAN Zong-yuan;LU Xiao-Jun;JIA Xin-chun;WANG Xiao-shu;BAI Wei(Institute of Computing Technologies,China Academy of Railway Sciences , Beijing 100081, China;School of Mathematics Science, Shanxi University , Taiyuan 030006 , China)
出处
《科学技术与工程》
北大核心
2018年第12期242-247,共6页
Science Technology and Engineering
基金
国家自然科学基金(U1334210)
中国铁路总公司科技研究开发计划(J2016X011)
中国博士后科学基金(2016M591355)资助
关键词
动数据收集
非线性规划
对偶分解
梯度下降
分簇
mobile data gathering
nonlinear programming
dual decomposition
sub-gradient descent clustering