Network Coverage Optimization And Location Algorithm For Forest Fire Monitoring

Forest fire monitoring has great ecological and economic value.With the latest technology of various kinds,the variable data in forest can be obtained more efficiently,so as to achieve good monitoring of fire and provide guarantee for the whole fire prevention work.In complex environment forest,deployed in the wireless sensor network(WSN)must have a good network coverage,network coverage is good or bad influence the network coverage,and then to significantly influenced on the overall cost and performance.Sensor nodes deployment randomness makes people cannot determine the location of the nodes in a network,in advance and positioning technology can provide more key location information for the network,is the foundation of a network a variety of application conditions.The thesis focuses on network coverage optimization and positioning problem,and the final research content and core results are as follows.This paper analyzes the network localization algorithm principle,at the same time,this paper analyzed the characteristics of forest environment and DV-Hop localization algorithm in this environment,according to its demonstrated proposed is applicable to the deficiency of the forest environment of network coverage optimization scheme and DV-Hop algorithm is improved.In the forest environment,a redeployment algorithm based on energy balance is obtained for the existence of static wireless sensor network.This method together with related nodes detection probability and energy distribution as a basis for the construction of a model,and then rely on binarization operation method to extract the cover on the edge of the hole,and triangle subdivision method is used to search for the ideal node location.Simulation analysis show that this scheme can be used in a relatively small number of nodes can be realized for the overall empty efficient repair,to better promote comprehensive network coverage,and prolong the life cycle of the network.In improving the research based on network coverage,aiming at the shortcomings of the DV-Hop localization algorithm,proposed an improved particle swarm based on the hybrid of DV-Hop localization algorithm,first of all,the information network of the Hop and jump every average error correction,and then the improved particle swarm optimization algorithm is used to locate the node coordinates,to replace the traditional maximum likelihood estimation method,optimization of the third phase of the algorithm.Simulation results show that the improved algorithm improves the positioning accuracy.In conclusion,the research results of this paper have been improved in terms of network coverage and positioning accuracy,which basically achieved the expected results.