Research On Optimal Deployment Of Nodes Suitable For Wireless Locationable Sensor Networks

Thanks to the rapid development of wireless communication technology,remote sensing technology,computer technology and microelectronics manufacturing technology,Wireless Rechargeable Sensor Networks(WRSNs)have emerged and been widely used.Unlike traditional battery-powered nodes,the sensor nodes in a wireless rechargeable sensor network collect energy through radio frequency signals and other energy sources.The charging process is less affected by changes in the surrounding environment,which can effectively extend the normal working life of the network.In WRSNs,node location information and deployment methods are important factors affecting charging time and charging efficiency.Research on node positioning issues and deployment methods has become a hot topic in this field.It should be pointed out that,in view of the wireless charging problem in WRSNs,the existing research usually fixes the position of the sensing node,and then deploys a mobile charging device in the network,and uses the path optimization algorithm to plan its optimal route,but does not consider the location of the sensing node the impact of deployment dynamics on charging issues.For the energy transmission model,the sensor node based on the adaptive distributed algorithm communicates with the surrounding common nodes by adjusting its own optimal data transmission rate,link flow and routing path,instead of building the energy transmission model based on the antenna radiation characteristics.Based on the above background,this paper focuses on the optimal deployment of sensor nodes in wireless localizable sensor networks as the research content.The key points include:1.Aiming at accurately estimating the energy transfer in omnidirectional radiation scenario,this paper studies the radiation characteristics of the half-wave dipole antenna,proposes the gain radiation model of the double-dipole antenna,and deduces the gain expression based on the antenna position and orientations as well as the estimation model of the receiving field intensity.2.Based on the above dual dipole antenna gain radiation model,a WRSNs problem model is proposed.Firstly,the mobile charger is used to charge the sensor node along the specified path,and the charging time limit method is adopted to propose the objective function based on the charging deactivation time.Then,through the channel transmission model between sensor node and common node,the geometric precision factor and system coverage degree are calculated.Finally,optimizing the location of the deployed sensor nodes to minimize the charging deactivation time,maximize the positioning accuracy and cover more normal nodes.3.In this paper,the multi-task evolutionary algorithm is adopted to optimize the node deployment of WRSNs,and the forward information migration co-evolution mechanism is proposed.According to the initial fitness value of different tasks,corresponding weights are configured in the same search space to assist the convergence of other tasks,and the implicit parallelism between tasks is utilized to complete simultaneous optimization.The simulation results show that compared with the traditional single-task optimization algorithm,the information forward migration multi-task evolutionary algorithm can effectively reduce the charging deactivation time,and improve the positioning accuracy and coverage.