Research On WRSN Charging Planning Algorithm Based On Energy Consumption Optimization And Analytic Hierarchy Process

With the rapid development and maturity of communication technology,embedded computing technology and sensor technology,wireless sensor network(WSN)plays a vital role in various fields.Due to the limited energy of sensor nodes themselves,they cannot guarantee long-term data collection work.Wireless Rechargeable Sensor Network(WRSN)has become the main solution to the energy-limited problem in Wireless Sensor Network(WSN),and has been a research focus for scholars both at home and abroad.In response to the energy consumption optimization and matching charging planning issues of traditional WRSN,in order to further extend the service life of WRSN and improve the energy utilization rate of mobile charging nodes(MC),This article proposes a Joint Region Division and Hierarchy Cluster Routing(JRDHCR)algorithm for joint region division and inter layer clustering routing,as well as a Mobile Charging Planning(CPUSDAHP)algorithm that considers preemptive update strategy and two-layer Analytic Hierarchy Process.The main research content of this article is as follows:Firstly,traditional WSN clustering routing algorithms still suffer from the problem of hotspot effects,and energy optimization methods have not adequately considered the charging planning energy utilization rate of mobile chargers(MCs).In this paper,based on the traditional WSN/WRSN region division method and clustering routing algorithm,an energy optimization algorithm for WRSN is proposed.This algorithm first analyzes the communication and energy routing of WRSN nodes and determines the dynamic cluster radius WRSN region division method.Then,a maximal cluster-based clustering algorithm is proposed to cluster the dynamic cluster radius divided WRSN subregions and improve the cluster structure through clustering optimization strategies.In the data transmission stage,a layer-by-layer routing mechanism based on relay routing interval division is proposed based on the traditional forward routing mechanism.Finally,the inter-layer routing mechanism is combined with the proposed region division and clustering routing methods to form the JRDHCR algorithm.A WRSN network model is built using Python to conduct parameter comparison experiments and algorithm comparison experiments on the energy optimization algorithms JRDFCR(Joint Region Division and Forward Cluster Routing)and JRDHCR combining joint region division and forward cluster routing.The experimental results show that the JRDHCR algorithm can reduce the overall energy consumption of the WRSN network and balance the node energy consumption between clusters and layers,and outperforms the JRDFCR algorithm and comparative algorithms in terms of WRSN lifespan,cluster structure,and MC charging efficiency.Furthermore,in the charging planning process,the target nodes for charging are not comprehensively considered,which leads to the problem of unbalanced WRSN lifespan and MC energy utilization rate.Based on the JRDHCR algorithm and the network model,this paper proposes a CPUSDAHP algorithm.Firstly,the decision-making attributes affecting the charging plan in the MC charging planning problem are hierarchically structured to construct an MC charging planning hierarchical structure model.Then,the weights of the decision-making factors for inter-cluster and intra-cluster charging plans are calculated separately,and the node charging plans and sorting are performed through the calculation of charging value and charging priority.Subsequently,a preemption update strategy integrating historical information is proposed to address the problem of long-term energy depletion in waiting clusters with relatively low charging value,and charging is also conducted during inter-cluster charging planning.Finally,an MC charging planning model is constructed and algorithm comparison experiments are conducted.The experimental results show that the CPUSDAHP algorithm proposed in this paper has improved the WRSN lifespan,overall remaining node energy,charging node selection,and charging efficiency compared to the comparative algorithms.Finally,based on the above research,the overall design of the WRSN energy consumption optimization and charging planning simulation system is carried out.A simulation system was built using Py Qt5,Qt Designer,and Python,and various sub modules of the overall system were tested.The test results showed that the overall system could meet the simulation experimental requirements.