Research On Hybrid Transmission Clustering Routing Algorithm With Efficient Energy Hole Avoidance

In recent years,with the large-scale production of low-cost and low-power micro-sensors,practical value and application prospects of wireless sensor network are very broad.But the battery energy of sensor node is highly limited,and the working environment is usually very poor,the feasibility of replacing the battery is not high.Therefore,how to efficiently use the limited energy to maximize the network life cycle is a key issue in the study of wireless sensor network.As some nodes prematurely depleted its own energy,resulting in the loss of its coverage area or data can not be sent to the sink,which produces energy hole phenomenon.Energy hole phenomenon is the focus and difficulty issue of wireless sensor network.In serious cases,the entire network can not work due to the phenomenon,resulting in a large number of remaining resources waste.In this paper,based on the low energy adaptive clustering hierarchy protocol,new clustering algorithms are designed from the cluster head selection,node deployment and data communication for the energy holes caused by the unbalanced energy consumption of nodes in WSN.Specific innovative work are as follows:(1)In order to solve the energy hole problem in the edge of the network,this paper proposes a clustering routing algorithm based on attractive factor and hybrid transmission(CRAH).The node residual energy and location are combined as a new index of reasonable selection of cluster heads by adopting the method of weighted sum in CRAH.The task of the cluster head is reassigned to the new selected fusion node.In the data communication phase,the attractive factor model is designed that fusion nodes adopt the mixed transmission mode for inter-cluster data communication,and improves Dijkstra algorithm to propose a new AF-DK algorithm.AF-DK algorithm selects the optimal forwarding path for data forwarding,saving the communication cost.(2)In addition,there is a problem that the data receiving rate of the base station is low in the CRAH,and the multi-hop transmission method will cause overload of nodes near the sink,resulting in the inner network of energy holes phenomenon.So this paper proposes an energy-hole avoidance algorithm based on swarm intelligence optimization and density control(EASD).The algorithm builds the node density decreasing model according to the forwarding energy consumption of the sensing data to ensure that the data forwarding load are shared by the corresponding number of cluster head nodes,and the load of each cluster head is balanced.In order to searchthe optimal path of multi-hop data communication between cluster heads and base station,group intelligence algorithm is optimized.The residual energy,location information,transmission distance and pheromone information of each neighbor node are added to improve the transition probability of ant to select the next hop node.When the pheromone update,combined with the packet receiving rate,considering the energy,path length and path quality,the reliability of the network forwarding path is improved.This solves the problem that the rate of base station receiving data is low,and balances the transmission energy between the cluster heads.(3)Finally,the simulation and experiment show that the two new algorithms can effectively solve energy hole problem and extend the network lifetime.At the same time,the two new schemes are compared with each other in terms of data delivery rate.It is proved that EASD solves the problem of low data reception rate of base station in CRAH and enhances path reliability.