Research On The Deployment Optimization Of Charger For Wireless Sensor Network

In traditional wireless sensor networks,sensors rely on batteries to provide power,but the limitation of their own energy storage shortens the life of the entire network,and seriously affects the performance of the network.With the development and maturity of wireless charging technology,wireless sensor networks use wireless charging technology to obtain power,thereby promoting the development of wireless rechargeable sensor networks.This new type of sensor network has gained widespread attention for improving the overall sensor life.However,the high energy loss of wireless charging technology has hindered its application in reality.In order to reduce the consumption of charging resources and improve the charging utility,this thesis studies two wireless charger deployment optimization issues.The main contents are as follows:The first part of this thesis studies the optimization of charger deployment for maximizing the charging utility.The problem solved in this part is given a charging power budget,and a set of sensors on the plane,the problem is that deploying the charger on the plane,that is,determining the location and charging power,so as to maximize the charging utility of all sensors.To address this problem,we converte the infinite solution space into a finite solution space through regional discretization,and then we reconstruct the problem.We prove that the problem is a monotonic submodule maximization problem,and a greedy algorithm with approximate ratio of(?)is proposed,whereis the error threshold for discretization of the plane area.The theoretical results are verified through simulation experiments.The experimental results show that the its performance can be improved by 300%compared with the random algorithm RPRL(random position and random level)algorithm.The second part of this thesis is the optimization of charger deployment with minimum charging power.The problem is that deploying the chargers with the smallest charging power at the candidate monitoring points,so that multiple mobile vehicles with rechargeable sensors have sufficient electric power to perform specific monitoring tasks along their respective periodic routes.This thesis constructs a mathematical model based on the actual charging and consumption of a vehicle,and formalizes the problem as an integer linear programming problem.By defining a submodule function,we obtain a greedy algorithm with an approximate ratio of 1+ln?,whereis the sum of the coefficients in the constraint.This thesis conducts validates the effectiveness of algorithm through simulation experiments.Compared with other greedy algorithms,our algorithm performance is improved by 30%,and the gap to the optimal solution is only about 10%.