Research On Charging Planning Method Of Wireless Rechargeable Sensor Network

With the wide application of wireless sensor network in the fields of ecological environment monitoring,urban facilities monitoring,industrial monitoring,earthquake fire monitoring and so on,the energy problem of sensor nodes is also prominent.The energy of wireless sensor nodes affects the life cycle of the entire network,which is one of the important factors that affect the network performance.As the energy supplement of wireless charging technology has the advantages of recyclable,schedulable,efficient and controllable,it has attracted the attention of experts at home and abroad,and wireless rechargeable sensor network has been formed.In the current wireless rechargeable sensor networks charging planning methods,the traditional schemes were to allow the single charger to periodically traverse the Traveling Saleman Problem(TSP)loop of all sensor nodes for charging,or to adopt First Come First Serve(FCFS),Nearest-Job Next with Preemption(NJNP),or other strategies to select the node order for charging.But they did not consider the problem of the driving distance constraint of charging vehicle,the power consumption of nodes,the importance of nodes and so on.Therefore,there are problems such as waste of resources and low charging efficiency.In view of the unbalanced energy consumption of sensor networks with sparse nodes,the parameters of adaptive benefits are defined according to the energy consumption model of nodes,and some nodes are selected to be charged according to this parameter in each round of charging process.Then,the charging planning problem is modeled mathematically,and a MMAS-CM algorithm based on MAX-MIN Ant System(MMAS)is proposed to optimize the income of the charging process.A more efficient charging path is obtained.Finally,compared with FCFS and NJNP,after several rounds of charging,the wireless sensor network charged by this algorithm has higher utility,smaller node residual life variance and lower node dormancy ratio.In view of the different importance of each node in the network when the nodes are dense,this paper comprehensively considers the connectivity critical degree and consumed energy ratio of nodes,and defines the importance degree of nodes to measure the importance of nodes.In this paper,a charging planning method for Critical Node First(CNF)is proposed in this paper.The network connectivity is maintained for as long as possible by selecting nodes with greater node importance,thus the disjointed and inactive time of nodes in the network are shortened.In order to maximize the total importance degree of all charging nodes,a mathematical model is set up,and a heuristic algorithm is proposed to solve the problem.The heuristic algorithm includes four steps:spanning tree growing,tour construction,tour improvement and tour optimization.Finally,compared with NJNP and TSP,CNF's performance is better.