Research On Multi-hop Wireless Charging Combined With Mobile Data Collection In Wireless Rechargeable Sensor Networks

With the rapid development of charging technology in wireless sensor networks,how to ensure the continuous operation of sensor network has become the current research trend.In order to extend the life cycle of sensor network,we have introduced wireless charging technology.At the same time,data collection is also a hot issue in wireless sensor networks.Considering the efficiency of traditional data collection models,this article only considers Sen Car's mobile data collection.This paper proposes new problems by combining multi-hop wireless charging technology and mobile data collection model.Firstly,this paper designs an optimal Sen Car distribution scheme,which proposes an approximate algorithm to solve the minimum amount of Sen Car required to finish all charging tasks in wireless sensor network under certain time and loss rate constraints.Next,we also design an optimal cost optimization plan.That is,the total time required to complete all charging tasks satisfies certain constraints,and comprehensively considers the cost of using the Sen Car.The planning scheme enables all charging tasks to be completed on the premise that a certain number of Sen Cars are used and the minimum total system cost required.The specific research work of this article is as follows:(1)By combining multi-hop wireless charging technology and mobile data collection model,a new optimal Sen Car distribution scheme is proposed.Firstly,we construct the energy consumption model under magnetic resonance coupling and calculate the charging efficiency of multi-hop wireless charging.Then,a multi-hop wireless charging scheme is constructed as a single-objective optimization problem,followed by an approximate algorithm to solve the problem.To ensure the continuous operation of the network,we firstly cluster the sensor nodes,calculate the charge loss of each node as a relay in each classification,and then use the node with the lowest charge loss as the “anchor”,and while Sen Car charges the “anchor”,it also collects the data generated by each sensor node.Next,cluster all selected “anchor points”,find a TSP path for each “anchor” in each category,and then get the minimum number of Sen Cars required to complete all charging tasks based on the capacity limitations of Sen Car.Finally,we simulate the proposed algorithm.The experimental results show that the strategy can complete all charging tasks with a minimum number of Sen Cars under certain conditions of time and loss rate constraints and Sen Car capacity constraints.(2)Present a new optimal cost optimization plan.Firstly,according to the relationship between energy consumption and energy replenishment,the number of Sen Cars required to complete all charging tasks can be approximated.Next,we cluster the sensor nodes and calculate the average loss of each node for each charging set.The node with the lowest average loss is first selected as the “anchor”,and while Sen Car charges the “anchor”,it also collects data from each sensor node.Then find a complete TSP path for all selected “anchors” and then consider Sen Car's battery capacity,Sen Car's mobile costs,and charging costs during multi-hop energy transfer to assign charging routes to a certain number of Sen Cars,ensuring that each path is within the scope of a Sen Car's service,to get the total cost of completing all charging tasks.Finally,we simulate the proposed algorithm.The experimental results show that under the condition that the strategy meets certain time constraints,using the appropriate number of Sen Cars can make the total cost of completing all charging tasks the lowest.(3)This article separately coded the two proposed algorithms on the Eclipse platform.Through a large number of simulation experiments,the effectiveness and feasibility of the proposed scheme are verified.