Statistical Analysis Of Event Monitoring Quality In Wireless Sensor Networks

As a new network technology,wireless sensor network is a hot research field at home and abroad.It is a new network technology,which can collect the data information distributed in the network in real time,and transmit the information to the gateway node,and finally complete the complex network monitoring and tracking work.This paper uses simulated annealing algorithm to analyze the monitoring quality of wireless sensor networks,studies the periodic switching and deployment optimization scheduling of wireless sensor networks,and obtains the high-quality monitoring network structure.The first chapter introduces the current research background and problems of wireless sensor network.It leads to the research content and purpose of the article.The second chapter is about the key technology of wireless sensor network and the estimation of statistical parameters.The third chapter is the establishment of wireless sensor network model.In a fixed target area of the event monitoring,build a node network model.In the process of monitoring,there will be a large number of sensors in the monitoring area may have a large overlap,through the design of optimized simulated annealing algorithm to improve the quality of monitoring.In the fourth chapter,the simulation of the experiment is carried out.Through the periodic switch and deployment optimization scheduling of the sensor,the ultimate goal is to save energy.In the research process,the innovation is to study the monitoring quality of wireless charging sensor network combined with statistical analysis.Through periodic switching and deployment optimization scheduling of sensors,the monitoring quality of the whole network is improved.OPNET software is used for simulation,and the visual graphics show the experimental results,which shows the rationality and optimization of the design of simulated annealing algorithm.In the fifth chapter,the future research of wireless sensor network is prospected.Considering the future cross layer optimization design ideas,the sensor node complex information acquisition process,more comprehensive consideration of the influence of various factors,in order to save time and energy.