Maximizing WCV Charging Benefits Based On Multiple Thresholds In Rechargeable Sensor Networks

In recent years,the continuous development of technology has enabled us to launch intelligent applications on smartphones,wearable devices,etc.,and integrate them into the Internet-of-Things.These applications usually rely on various sensor nodes to capture and generate a large amount of data from multiple dimensions,so as to detect,identify and classify targets with high accuracy.However,wireless sensor nodes are only equipped with limited power supply.According to the current research on energy consumption balance,even if the energy consumption of nodes in the whole network can be balanced as much as possible by adopting different transmission strategies,node deployment strategies and non-uniform clustering algorithms,it still can not meet the needs of large-scale and long-running networks.With the progress of research,wireless rechargeable sensor networks(WRSNs)has gradually become one of the effective means to solve this kind of problem.Wireless charging vehicle(WCV)moves periodically or randomly in the network to provide services for nodes that need energy supply,so as to effectively prolong the life of the network.However,most of the current work aims at all nodes do not die,that is,WCV is required to respond to the charging request of any node anytime and anywhere.For WCV with limited energy storage,slow movement and bottleneck in charging speed and efficiency,it is very difficult to achieve this goal.In addition,almost all algorithms set the charging request threshold of the node to a unified value,which not only does not take into account the balance between the node data load and the energy it needs to replenish,but also may cause the explosive growth of the number of energy replenishment requests in a short time,which increases the complexity of system scheduling.Therefore,how to efficiently use the energy of nodes in the network to maximize the charging benefit is an important problem in the research of wireless rechargeable sensor networks.This thesis proposes a mechanism to maximize WCV utilization based on multiple thresholds,designs a reasonable and balanced node data upload path,and determines the number of key nodes in the network.Subsequently,the dual charge request threshold is set for the node to meet the energy replenishment requirements of different energy consumption nodes simultaneously,thereby equalizing the remaining life cycle of the node.Moreover,the current location of WCV is considered,and a sequence expansion method of nodes to be charged based on the location of WCV is designed to maximize the charging efficiency of WCV.On this basis,a strategy to save dying nodes is further proposed to minimize the number of dead nodes,so as to prolong the running time of the network as much as possible.Simulation results show that under the influence of various factors such as different charging power and moving speed,WCV has better performance on node failure rate than Nearest-Job-Next with Preemption(NJNP)and First Come First Server(FCFS).Compared with these two methods,the method in this thesis also greatly increases the number of nodes that WCV can serve and shortens the average driving path of WCV charging service,which leads to the improvement of WCV charging efficiency.Compared with NJNP and FCFS,the node failure rate of this algorithm is reduced by about 15% and 25% respectively,the average number of nodes served is increased by about 45% and 50% respectively,and the average driving path of WCV charging service is reduced by 34% and 58% respectively.