Research On On-demand Charging Strategy For Rechargeable Wireless Sensor Networks

In the information age,in order to conform the trend of intelligence,wireless sensor networks are widely used because of their low cost,low power consumption and self-organization characteristics.However,the wireless sensor battery has limited capacity and is difficult to replace frequently.In addition,the wireless sensor network energy consumption is uneven,which will accelerate the exhaustion of some nodes,resulting in paralysis of the entire network.Limited energy has become the primary factor restricting the development of wireless sensor networks.With the development of wireless energy transmission technology,rechargeable wireless sensor networks that use the mobile charger to charge the sensor nodes actively make it possible for wireless sensor networks to continue working.However,under the existing research conditions,the parameters of mobile power parameter configuration,mobile power energy distribution,and mobile power charging sequence in the rechargeable wireless sensor network need to be further explored.This article takes the rechargeable wireless sensor network as the background,the main work and contribution can be summarized as the following aspects:(1)Based on the research of the development status of rechargeable wireless sensor networks,this paper classifies the existing charging strategies and points out the different scenarios they can adapt to.(2)Aiming at the large density distribution of sensor nodes,a single mobile power charging strategy based on charging requirements is proposed.Convert the optimal stop point problem for mobile charger to an overlap problem.According to the distance between the sensor and the power source,the charging power is discrete,and the charging level function is proposed,innovatively classify the charging level function as the coverage radius in the coverage problem.Use genetic algorithm to solve the approximate solution of the parking point of mobile charger,and finally use elastic network algorithm to plan the shortest path of mobile charger.(3)For a sensor network with a large number of nodes and a large scale,a charging strategy based on energy prediction for on-demand charging of multiple mobile charger is proposed.In this paper,the Markov prediction model is used to predict the energy consumption rate of the sensor node.Calculate the weight according to its energy consumption rate and residual energy,and select the top k nodes with the lowest weight to charge;under the premise of ensuring that all charging tasks are completed,a greedy heuristic algorithm is proposed to solve the minimum amount of mobile charger and plan the shortest charging path for it.(4)Through the comparison and analysis of simulation,it is proved that the two charging strategies proposed in this paper can guarantee the continuous and normal operation of the network.The single MC charging strategy based on charging demand degree can effectively improve the energy utilization rate of mobile charger and reduce the charging delay for scenarios with high node distribution density.The multi-MC charging strategy based on energy prediction can effectively reduce the number of mobile charger and maintain a high energy utilization rate of mobile chargers.