Research And Application Of WSN Clustering Routing Algorithm Based On Energy Balance In Landslide Monitoring System

China’s geological structure is characterized by complexity,with a wide distribution of various geological hazards.Among them,landslides are the most common natural disasters in mountainous regions,causing significant damage to surrounding infrastructure and,in some cases,resulting in casualties.Existing landslide monitoring technologies are often characterized by high equipment costs,poor performance,and low real-time capabilities,resulting in inadequate monitoring of landslides.This thesis designs and implements a landslide monitoring system based on the characteristics of wireless sensor networks(WSN)to solve the problems of existing monitoring system.The main research contents of this thesis are as follows:Firstly,this thesis analyzes in detail the purpose and importance of adopting WSN technology in landslide monitoring system.Starting from the architecture and key technologies of WSN,the superiority of applying WSN technology in landslide monitoring is discussed,with a focus on the routing techniques within WSN.Secondly,in order to select the cluster heads more reasonably and plan the data transmission paths from the cluster head to the base station to avoid unbalanced energy consumption of the sensor nodes in the network,a clustering routing algorithm based on energy balance(CRAEB)for WSN is proposed.At the cluster head election stage,to address the shortcomings of the conventional butterfly optimization algorithm,which is prone to premature convergence,a dynamic opposite learning strategy is invoked to improve the quality of the initial solution,the global search formulation is improved using nonlinear inertia weights,and the firefly perturbation is added to improve the population diversity.When designing the fitness function,four factors are considered: the size of the residual energy of the nodes,the balance of the residual energy of the selected nodes,the compactness of the clusters,and the distance between the nodes and the base station.At the inter cluster routing phase,the improved shuffled frog leaping algorithm is used for path planning,and the shuffled frog leaping algorithm is improved by using a linear bootstrap strategy instead of randomly generating new solution,performing a dimension-by-dimension variation on the optimal solution,and using the standard deviation of residual energy at the cluster head as the fitness function.Simulation experiments show that the algorithm proposed in this thesis equalizes the energy consumption of nodes in the network to a certain extent and extends the life cycle of the network.Finally,the proposed algorithm is applied to monitor landslide scenarios,and a landslide monitoring system is designed and implemented accordingly.The CC2530 chip is selected,and multiple types of sensors are deployed for data collection based on practical requirements.The client side of the monitoring system adopts a B/S architecture and the software program is mainly developed in Java.The test proves that the system runs stably and the energy consumption of the nodes is balanced,which can meet the practical requirements of landslide monitoring.