| Air pollution has a major impact on human health,plant growth,weather and climate.Air is a necessity for human survival,and air pollution in cities must be managed reasonably and effectively.Therefore,more people attach importance to the analysis and monitoring of air quality.Wireless Sensor Networks(WSN)are widely used in air quality monitoring applications.In order to better reflect the quality of air,a comprehensive sensor network needs to be deployed to monitor air quality in a timely and accurate manner,and then effectively develop appropriate measures to control air pollution.Firstly,this paper mainly studies the optimization problem of WSN node deployment for air quality monitoring.According to the environmental characteristics of the monitoring area,a reasonable deployment strategy is designed to deploy as few sensor nodes as possible in the monitoring area,so as to reduce the deployment cost on the premise of satisfying the network connectivity.Secondly,at present,most of the research on the optimization of WSN node deployment adopts a simple disk node coverage model or a probability perception model.This research has ignored the spatial synergistic perception effect between sensor nodes,and failure to fully play to the utilization of sensor nodes,which leads to an increase in deployment costs.In this paper,the sensor node adopts the Confident Information Coverage model(CIC)as the node coverage model,and combines the environmental characteristics of the deployment area to formulate the coverage constraints of the sensor node in the programming.The sensor network connectivity constraints are formulated using the definition of network flow.According to the CIC coverage requirements and network connectivity requirements of sensor nodes,the Integer Linear Programming with optimization objective(CICILP-COST)and Integer Linear Program with estimate error as optimization objective(CICILP-ERROR).Thirdly,considering that integer linear programming is an NP-hard problem,heuristic algorithms based on variable relaxation method and dichotomous search method(CICVR-COST,CICDS-ERROR)are designed in this paper for two kinds of integer linear programming in order to handle large-scale deployment applications,respectively.Finally,this paper conducts a series of simulation experiments to verify the effectiveness of the two deployment optimization algorithms from different observation dimensions.The experimental results show that the trusted information coverage node deployment strategy proposed in this paper can effectively reduce the number of sensor nodes deployed and significantly improve the utilization rate of sensor nodes while meeting the monitoring area coverage requirements. |
