Research On Node Routing And Coverage Optimization In Wireless Sensor Networks

With the increasing development of wireless sensor network(WSN),it is gradually used to monitor,track,perceive,measure and collect real-time data in our daily life,such as intelligent building,agriculture and forestry monitoring,industrial process monitoring and so on.These applications often need to deploy a large number of sensor nodes with certain physical perception and communication computing capabilities to replace human perceptual monitoring.However,it is a challenging problem to find the best deployment location of nodes in large-scale wireless sensor networks.Secondly,the unreliable link communication in the routing process of wireless sensor networks will lead to low data transmission efficiency and uneven energy consumption,which will affect the efficiency and life cycle of the whole network.In addition,in large-scale wireless sensor networks,the coverage,connectivity,life cycle,energy consumption and cost of the deployed nodes are closely related to the quality of service,and optimizing these performance indicators at the same time is a challenging task.In order to solve these problems,this paper has carried out the following work:(1)Aiming at the problem of low energy efficiency in the routing process of wireless sensor networks,a routing game algorithm based on link quality is designed.Firstly,the index to evaluate the link quality is defined.Secondly,the link quality,node residual energy and minimum hop forwarding strategy are integrated into the utility function to establish a game model to determine the best next-hop transmission node.Finally,according to the analysis of the existence of Nash equilibrium in the game,the best routing transmission path is obtained.In the simulation experiment,the influence of the change of link quality parameters on the performance of the algorithm is analyzed,and the proposed algorithm is compared with NWPSO algorithm and LEACH-IMPT algorithm in three aspects: the number of surviving nodes,network lifetime and network energy consumption.The results show that the proposed algorithm can effectively balance network energy consumption and prolong network life cycle.In addition,according to the routing path obtained in the simulation experiment,the optimality of the link quality is verified in the real experimental environment,and the experimental results prove the feasibility of this method in practice.(2)In order to solve the problem of uneven network load caused by cluster head nodes when wireless sensor networks are deployed in banded areas,a method of optimal coverage deployment of WSN nodes based on diamond partition is proposed.Firstly,the energy consumption model of cluster head suitable for banded region is established,and the research area is clustered equidistant in the way of diamond partition.On this basis,the number of cluster head nodes in each cluster is optimized according to the distance from the base station,and the replacement mechanism of non-uniform deployment of cluster head nodes is adopted.In addition,through the analysis of network energy consumption,it is proved that this method is superior to the network life cycle in the case of uniform deployment.Simulation results show that the proposed method can not only improve the network utilization,but also effectively prolong the network life cycle.(3)Aiming at the problem of multi-objective coverage optimization in 3D environment,a multi-objective coverage optimization method in 3D wireless sensor networks is proposed.First of all,the performance indicators in the multi-objective optimization problem are modeled and formulated,and an experimental platform is built to verify the theoretical model in practice.On this basis,combined with simulated annealing algorithm,particle swarm optimization algorithm is improved,and a multi-objective coverage optimization method: MOOCDA is designed.The proposed method can provide the best solution according to different deployment requirements such as coverage,connectivity and network topology,and MOOCDA can also give a solution that adapts to the needs of users according to the weight value of specific performance indicators.The experimental results verify the effectiveness of the proposed method,and the superiority of the proposed method is proved by comparison with other research methods.