Research On Deployment And Coverage Of Wireless Sensor Networks In Aircraft Cabins

At present,with the vigorous development of civil aviation industry,aircrafts gradually become a comfortable,reliable and economical means of transportation.However,fire hazards exist since the civil aviation aircrafts emerge,and this problem have never been well solved.The fire in aircrafts have the characteristics of high concealment,rapid spread and difficult rescue,once it happens,serious losses cant be avoided.The current monitoring for aircraft fire mainly uses single-point sensor,which will lead to false alarms.However,wireless sensor networks(WSN)composed of a large number of sensor nodes can effectively solve these problems.Therefore,how to deploy wireless sensor networks without monitoring vulnerabilities,with high monitoring accuracy,strong resistance to failure,and sufficient continuous service time has become a popular topic.Therefore,this thesis focuses on the deployment of wireless sensor networks in aircraft cabins.This thesis divides the deployment of wireless sensor networks in aircraft cabins into two branches: static deployment and dynamic deployment.In terms of static deployment,WSNs satisfying K-coverage are deployed using Linear Limit Monte Carlo Artificial Bee Colony algorithm.This algorithm enhances the potential mining ability of the traditional ABC algorithm,and can realize K-coverage with fewer sensor nodes.In terms of dynamic deployment,from the perspective of extending the life of the network,the operation state of each sensor node is dynamically allocated through the Improved Binary Artificial Bee Colony-Low Energy Adaptive Clustering Hierarchy algorithm.Besides,the thesis achieves K-coverage for the monitored area with probability pA.This algorithm generates a subset of operating nodes and a subset of cluster head nodes for global optimization.On the premise of the coverage index satisfying,the proposed method can allocate each node reasonably,which can balance the network load,reduce network energy consumption and extend the network life.