| Wireless Sensor Network is composed of a large number of sensor nodes deployed in the monitoring area and is widely used in fields such as environmental monitoring,industrial process control,and military surveillance.Due to the small size,limited battery energy,and difficulty in the replacement of sensor nodes,how to effectively utilize node energy and extend the network lifetime has become an urgent problem.In the process of WSN operation,data transmission consumes most of the node energy,so selecting an efficient routing algorithm has a significant impact on the network lifetime.If the routing path is too far,long-distance data transmission will cause rapid energy consumption of the nodes.If the routing path stays on sensor nodes with low energy for a long time,these nodes will quickly die due to receiving and forwarding too much data.Therefore,this paper proposes two improved algorithms based on the existing clustering routing algorithm to balance node energy consumption and extend the network’s lifetime.(1)Multi-hop routing algorithm based on sparrow search algorithm to optimize fuzzy Cmeans.In the clustering stage,the proposed algorithm first calculates the optimal number of clusters for the current network nodes and then uses the FCM algorithm optimized by the sparrow search algorithm to cluster the nodes,aiming to solve the problem of the FCM algorithm’s sensitivity to initial clustering centers.In the cluster head selection stage,the algorithm introduces a dual cluster heads mechanism to alleviate the energy load of a single cluster head.The main cluster head is responsible for collecting,merging,and sending data,while the secondary cluster head is responsible for data relay.To select the primary and secondary cluster heads,two fitness functions are constructed based on the remaining energy of the nodes,the intra-cluster communication distance,and the distance from the nodes to the base station,and the primary and secondary cluster heads are selected based on the different fitness functions.In the data transmission stage,the algorithm calculates the weight of inter-cluster communication based on the remaining energy of the secondary cluster head,the energy consumption of inter-cluster communication,and the communication load of neighboring cluster heads,and uses the minimum spanning tree to find the optimal path for multihop routing.(2)WSN clustering routing algorithm based on improved K-means and entropy weight method.In the clustering stage,the proposed algorithm uses the density method and the max-min distance to improve the K-means algorithm in order to overcome the problem that the traditional Kmeans algorithm is sensitive to the initial clustering centers.In order to balance the energy consumption of cluster heads,a redistribution scheme is used to optimize the structure of clusters and balance the number of nodes in each cluster.In the cluster head selection stage,the nodes’ remaining energy,intra-cluster communication average distance,distance to the base station,and the number of times selected as a cluster head are used as evaluation indicators.The entropy weight method is used to calculate the weight of each node’s indicators to select a more reasonable cluster head.In the data transmission stage,the algorithm constructs a communication consumption function to select relay nodes based on the residual energy of cluster heads and the transmission distance of data.This paper proposes two improved routing algorithms to balance network nodes’ energy consumption and extend network lifetime.These two algorithms start with three aspects: node clustering,cluster head selection,and inter-cluster routing.The improved clustering algorithm is applied to network node clustering,and multiple factors are dynamically combined to select cluster heads.Finally,the selected cluster head nodes and relay nodes are used to construct the best route for data transmission.The simulation experiments evaluate the improvement effect of the two algorithms in several aspects,such as the number of surviving nodes,the remaining energy of the network,and the number of packets received by the base station,for two-dimensional and threedimensional scenarios,respectively.The experimental results show that the proposed algorithm can effectively balance node energy consumption and extend network lifetime. |
