摘要
针对现有无线可充电传感网络的节点优化部署方法中存在的收信能量估计模型未考虑实际商用天线的定向辐射特征、优化目标未考虑节点部署方式对定位精度和覆盖程度的影响、节点部署方法寻优精度有待进一步提升等问题,研究适于无线可充电传感网络的新型节点优化部署方法。以精确估计收信能量为目标,提出基于双偶极子天线的收信能量估计模型;提出传感节点失活时间、普通节点定位精度、普通节点覆盖程度的评价方法,完成优化目标函数的构建;提出融合信息正迁移机制的多任务进化算法,求解优化目标函数,通过优化部署传感节点的位置实现节点失活时间最小化、定位精度最大化、覆盖程度最大化。仿真结果显示:当普通节点数为36时,相比于传统单任务进化算法,本文算法的节点失活时间降低了32%,定位精度提高了23.5%,节点覆盖程度提高了12%。
Aiming at the problems of wireless chargeable sensor networks node deployment methods such as the received energy estimation model does not consider the directional radiation characteristics of actual commercial antennas,the optimization goal does not consider the impacts of nodes deployment on positioning accuracy and coverage,and the optimization performance of the node deployment method needs to be further improved,the novel nodes deployment optimization method for wireless chargeable sensor networks is studied.Aiming at achieving the accurate estimation of received energy,the received energy estimation model based on a dual dipole antenna is proposed.The evaluation methods about the deactivation time of sensor nodes,positioning accuracy and coverage of normal nodes,are proposed.The optimization objective function is accordingly established.A multifactorial evolutionary algorithm incorporating a positive information transfer mechanism is proposed to solve the objective function.By optimizing the location of the sensor nodes,the solution with minimal node deactivation time,maximal positioning accuracy and coverage are achieved.Simulation results show that,compared with the single-objective optimization algorithm,the node deactivation time of the proposed algorithm is reduced by 32%,the positioning accuracy is improved by 23.5%,and the node coverage is increased by 12%.
作者
史伟光
李耀辉
王山川
SHI Wei-guang;LI Yao-hui;WANG Shan-chuan(School of Electronics and Information Engineering,Tiangong University,Tianjin 300387,China)
出处
《天津工业大学学报》
CAS
北大核心
2021年第2期64-73,共10页
Journal of Tiangong University
基金
天津市自然科学基金资助项目(19JCQNJC03300)。
关键词
无线可充电传感器网络
偶极子天线
定位精度
覆盖程度
多任务进化
wireless chargeable sensor networks(WRSNs)
dipole antenna
positioning accuracy
coverage
multifactorial evolutionary
