Research And Analysis Of Improved Routing Protocol Optimization Algorithms Based On Wireless Sensor Networks

Wireless sensor networks are wireless communication networks formed by self-organization of a large number of low-power nodes,which are widely used in various fields such as aerospace,military,medical,and environmental protection.The internal nodes of the sensor monitor information in the monitoring area,and send data to users through the network.Due to the difficulty of energy supply for internal nodes in sensors,the harsh environment of node random distribution,and the single restriction of local topology information on routing protocol design,how to effectively reduce energy consumption and select the global optimal path is currently the focus of research.Based on the improvement of the Leach protocol,the Leach protocol proposes a "round" operation to divide the nodes in the monitoring area into cluster areas,which improves network performance compared to traditional planar routing protocols.However,the Leach protocol cluster header division is unreasonable,and data transmission uses a single hop method to increase the energy load.Therefore,the Leach protocol is improved.The main research content of this thesis is as follows:Analyze the internal structure and topology of wireless sensor networks.Unlike traditional networks,which are address centric,wireless network sensors are data centric,and routing protocols are key factors in sensor design.Introduce several typical planar and layered routing protocols,and introduce the Leach protocol in detail and conduct simulations.An improved Leach-IACA protocol based on the bionic ant colony algorithm and Leach protocol is proposed,which introduces multiple energy control factors during the cluster head establishment phase,fully considering the energy factor of the cluster head node,and avoiding low energy nodes being selected as cluster head nodes.In the data transmission stage,the fitness function is improved to plan multi hop routing between cluster heads,and the pheromone concentration is improved to avoid routing selection falling into a local optimal solution.GTACO algorithm is proposed based on grouping teaching mechanism and improved particle swarm optimization algorithm.Grouping teaching mechanism improves ant path selection learning ability for global search.In the inter cluster transmission stage of Leach protocol,particle swarm optimization algorithm fitness function is improved,fully considering the energy information of the next hop node and the distance between nodes.The two combine to output the global optimal path for data transmission to avoid excessive energy loss.Finally,through simulation using MATLAB software,the number of remaining nodes in the sensor network,the times of data can be received by the base station,then the overal energy consumer of the network are analyzed and compared.The results show that the GTACO algorithm based on the grouping teaching mechanism and the improved particle swarm optimization algorithm is superior to other protocols in network performance.