Wireless Sensor Network Routing Optimization And Charging Strategy Research

The main role of Wireless Sensor Network(WSN)is to collect various environmental data in the sensing coverage area and transmit the data to the target user after simple processing.Due to the limitation of size,the nodes cannot carry large capacity batteries to ensure the energy supply,so energy saving is the main challenge for WSNs.In this paper,we also address the energy consumption of WSNs by optimizing the routing algorithm of the network and introducing wireless chargers to recharge and replenish the energy of the network,both of which aim at extending the network life cycle and improving the network operation efficiency.The optimization of network routing is mainly carried out from the selection of cluster headers and the transmission path of packets.In this paper,we propose an Energy Distance-based Cluster Head selection and Routing(EDCR)protocol based on the energy and mutual distance of sensor nodes,which uses the remaining energy of the nodes,the relative Euclidean distance between the nodes and the base station,and the cluster center of mass to extend the WSN life cycle.Since nodes consume a lot of energy in the clustering phase,to avoid this,this paper introduces a new clustering method based on the fuzzy C-mean classification technique,i.e.,a new fitness function is proposed to select CHs,and then a group routing strategy is used to transmit data between nodes and destinations using the shortest path method,which reduces the energy consumption of CHs by using multi-hop communication.Simulation results show that the EDCR protocol can save the residual energy of the network,improve the network coverage delay and extend the network lifetime compared with other similar algorithms such as FCM,REHR and CCA-GWO.The use of remotely controlled carriers carrying wireless chargers to charge and replenish the nodes is a method that can solve the energy constraint of nodes at the source.At present,we mainly focus on the optimization study of charging planning of mobile chargers and design efficient mobile charging plan to significantly extend the network survival time.In this paper,we propose a Multi-Attribute Decision Making(MADM)based mobile charging scheduling strategy,which solves the complex charging decision problem by coordinating multiple network attributes and evaluating various network attributes by AHP and TOPSIS,i.e.,residual energy,distance to the charger,energy consumption rate and neighborhood energy weights to determine the appropriate charging scheduling strategy.By comparing the simulation results with related methods,the results show that the proposed scheme has improved in various performance metrics.