Research On WSN Node Deployment Strategy For Railway Environmental Monitoring

With the rapid development of high-speed railway technology in China,the improvement of train speed has brought great convenience to people's daily travel.Because of the increasing demand for travel,the construction mileage and train operation of high-speed railway are increasing year by year.At the same time,the environmental safety of train operation has also attracted much attention.In the process of train operation,real-time monitoring of railway environment is the key to ensure the safety of train operation.Because most of the railway tracks in China are located in mountainous and plateau areas,there will be problems such as high network cost,complex deployment and difficult maintenance when using traditional wired monitoring equipment to monitor railway environment.Therefore,wireless sensor network(WSN)is introduced into railway environmental monitoring.WSN has the characteristics of self-organization,dynamic topology transformation,simple network structure and low deployment cost.However,WSN also has shortcomings,such as small size and limited resources.When deployed in the field environment,only battery-powered sensor nodes can be used,which highlights the "energy hole" phenomenon in the network and reduces the network performance of WSN.In this thesis,the WSN deployed in railway environment is studied.Based on WSN and clustering topology,and aiming at solving the problem of "energy holes",a node deployment optimization algorithm based on non-uniform clustering is proposed.By comparing with the existing WSN node deployment algorithm deployed in railway environment,the superiority of the proposed algorithm is proved.The research results are as follows:(1)The railway environment is analyzed.According to the characteristics of the railway environment,a uniform deployment model of the basic nodes of wireless sensor network is established.WSN deployed in the railway environment needs to meet the requirements of no blind area coverage in the monitoring area.In addition,the network needs to meet the requirements of simple structure and high stability.The uniform deployment model of base nodes can meet the requirements of WSN in railway environment.(2)This thesis introduces the existing WSN node deployment algorithm which can be used in railway environment.This algorithm grouped cluster-head nodes in the network on the basis of uniform clustering,enabling multiple links in the network to transmit data at the same time,and reducing network energy consumption by sharing the amount of data transmitted by cluster-head nodes.The algorithm has some effect in reducing network energy consumption,but the phenomenon of "energy hole" still exists in the network.To solve this problem,this thesis proposes a node deployment algorithm based on non-uniform clustering and its optimization algorithm.The algorithm is based on non-uniform clustering of the basic nodes in the network.The cluster head nodes are deployed in the center of the cluster.By adjusting the size of the cluster,the amount of data transmitted by the cluster head nodes is controlled to achieve the goal of balancing the energy consumption of each cluster head node in the network.The optimization algorithm for this algorithm is based on the algorithm,which optimizes the location of cluster head nodes,optimizes the communication distance between cluster heads by adjusting the location of cluster head nodes in the cluster,and controls the amount of data and transmission distance of cluster head nodes,so as to achieve the goal of reducing energy consumption on the premise of balancing the energy consumption of cluster head nodes.(3)Using the simulation software of MATLAB to simulate the two algorithms and the comparison algorithm,verify the effectiveness of the proposed algorithm.The simulation experiment mainly compares the network formed by three node deployment algorithms under the same simulation parameters from three aspects: network energy consumption,network lifetime and network efficiency.In addition,the scalability of the three algorithms is simulated and compared.The simulation results show that the proposed node deployment optimization algorithm based on non-uniform clustering can effectively balance and reduce the energy consumption of nodes,prolong the network life by 10.7%,and improve the network efficiency by 8.89%,and the algorithm has the best scalability.