Research On Energy-optimized Clustering Routing Algorithm For Wireless Sensor Network

With the development of embedded technology,the computing space based on software and hardware is increasingly merging with the physical space of the real world.Cyber-physical systems emphasize the close interaction of humans,the computing world,and the physical world to achieve a theoretical system and technical framework that integrates information and industrialization,including computing,communication,control,and sensing.Wireless sensor networks are an important application in the perception layer of cyber-physical systems.It mainly monitors and records the physical conditions of specific areas through sensors,and then transmits the collected data to the main control node in a wireless communication manner.It is a distributed,self-organizing,multi-hop sensing network.Wireless sensor nodes in wireless sensor networks are characterized by their small size,low cost,and usually random deployment in unmanned environments.Therefore,the micro-batteries embedded inside the nodes have very limited energy and are not necessary to replace.The failure of nodes due to energy depletion can lead to coverage holes in the target area,which reduces the effectiveness of the data monitored by the network.Therefore,energy is the most precious resource in wireless sensor network nodes,and whether the energy in the network can be efficiently utilized and whether the energy of the nodes can be evenly consumed determines the working time of the wireless sensor network.The clustering routing algorithm in wireless sensor networks aims to reduce the energy consumption of data transmission by changing the network topology.Due to its easy combination with data fusion,coverage optimization,and node positioning technologies,it has received extensive research and application.This thesis starts with the energy-saving clustering routing algorithm in wireless sensor networks with the goal of extending the effective sensing time of the network.It comprehensively considers how to shorten the communication distance between nodes,balance the energy consumption between nodes,and optimize the energy utilization efficiency of nodes.It conducts optimization research on the three stages of cluster formation,cluster head selection,and communication path selection,and proposes the following two optimization design schemes:1.In order to address the two problems of how to evenly cluster the nodes in the network and balance the loads between nodes within the cluster through cluster head rotation,an energy consumption optimized wireless sensor networks routing algorithm based on virtual force clustering is proposed.First,with the goal of minimizing the total energy consumption of the network,a dynamic calculation method for the optimal number of clusters is given.Second,a centralized clustering strategy based on virtual force is proposed to achieve a more uniform clustering of the network.Then,an ant-lion optimization algorithm is introduced to calculate an optimal set of virtual force weight factors to avoid the problem of uneven deployment of virtual cluster heads when virtual force weight factors are preset according to human experience,even when the virtual cluster heads reach a state of force balance.After the network completes clustering,a distributed dynamic cluster head election strategy is designed by considering the distance from nodes to virtual cluster heads,remaining energy,and distance to the base station.Finally,through simulation experiments,it is verified that the clustering effect of the algorithm is better,the energy utilization efficiency of the network is higher,and the effective working time of the network is significantly extended.2.In response to the problem that cluster heads are overloaded with tasks and the blind adoption of a multi-hop strategy is prone to energy wastage,an dual head wireless sensor networks routing algorithm based on optimized cluster analysis for clustering combined with adaptive relay strategy is proposed,considering the division of responsibilities of the cluster head and the determination of the applicability conditions of multi-hop strategy,it optimizes the cluster structure,cluster head selection,and communication path selection of wireless sensor network clustering routing algorithms.In the clustering stage,a dual cluster head model is introduced,and a calculation method for the optimal clustering scale under different scenarios is constructed.Then,an improved arithmetic optimization algorithm is used to optimize the fuzzy C-means algorithm,which improves the stability and uniformity of the centralized clustering of the fuzzy C-means algorithm,and the mechanism of centralized clustering avoids the broadcast energy consumption of frequent clustering.In the cluster head election stage,independent cluster head evaluation functions are designed according to the different working tasks of the internal and external cluster heads.The tasks are assigned to various nodes while shortening the communication distance of the cluster head,and the mechanism of distributed election reduces decision-making costs.In the data transmission stage,the adaptive distance usage conditions for multi-hop relay strategies are defined.The external cluster head selects the next external cluster head based on the position and energy consumption rate under the premise of meeting the above conditions to avoid premature overload of the external cluster head.Finally,through simulation experiments,the proposed algorithm effectively balances the load between nodes,improves energy utilization efficiency,and prolongs network life.It also has good robustness in the face of different network scenarios.