Research On Energy Efficiency Optimization Algorithm In Wireless Sensor Networks

Wireless Sensor Networks(WSN)consist of a large number of sensor nodes designed to transmit the specified environmental state data in the target area to the base station through a dynamic self-organizing network to support the depth perception of the target area by the master station.WSN is used in all major fields because of the advantages of low energy consumption,small size and easy installation of sensor nodes,but the sensor nodes have limited energy reserves.How to improve the network energy utilization efficiency and maximize the use of its limited energy to extend the network life is an important research topic for WSN to achieve wider application.Although wireless rechargeable sensor networks have emerged,the charging effect is limited by the environment and resource input,so the study of energy-efficiency optimization algorithms for WSNs is still of great importance.R esearch on cluster routing algorithms in fixed base station scenarios and mobile base station path planning methods in mobile base station scenarios can both help improve WSN network energy efficiency.The main innovations and work points of this thesis are as follows:In the fixed base station data scenario,an equilibrium mechanism-based energy-efficient clustering and routing algorithm is proposed.In the clustering process,the expected cluster formation radius is determined based on the location factor and coalescence factor to achieve the cluster head load balancing at nearbase station nodes and dense nodes.Then the iterative algorithm is designed with the objective of energy balancing to achieve network-oriented adaptive clustering.Finally,to further optimize the energy efficiency of the network,an energyefficient inter-cluster routing strategy for all cluster heads is proposed based on the clustering results.The inter-cluster routing cost is calculated by accounting for the expected residual energy and path energy consumption of cluster heads,and then the optimal next-hop is determined for each cluster head to improve the energy balance among cluster heads.Simulation results show that this algorithm can effectively achieve energy-efficiency optimization of WSN for fixed base station data collection.In the mobile base station scenario,an energy-efficiency optimizationoriented mobile data collection strategy is proposed.Firstly,by considering the heterogeneity of energy distribution,the location of clustering center is determined based on energy valley coefficient,and the anchor distribution is optimized by improving K-means algorithm to achieve network energy balance;Then based on the anchor point distribution,the path planning of mobile base stations is realized with the objective of minimizing the mobile path length;Finally,adaptive dual-mode distributed routing is designed to achieve energyefficient mobile data collection.The simulation results show that the algorithm can effectively realize the energy-efficiency optimization of WSN for mobile base station data collection.