Research On WSN Mobile Data Collection Algorithm In Dangerous Scenarios

Data collection technology in wireless sensor networks is a hot topic at present.It monitors a certain area through a large number of sensor nodes and transmits the data to a remote base station for processing.In traditional networks,nodes are deployed and remain static,sending data to sink through multi hop transmission.In this data collection mode,the nodes near the aggregation node(sink)need to transmit more data than other sensor nodes in the network,thus forming a network hot zone so that the energy of these nodes will decline rapidly.In order to make the energy consumption of the network more balanced,using mobile nodes for data collection has become a research hotspot in recent years.However,in many practical applications with large network scale,Due to the limitation of its capacity and space,mobile nodes need to send the collected data to sink for processing in a certain time delay range,otherwise,these data information will be meaningless.Therefore,this paper studies the optimal path of mobile nodes on the basis of reducing network energy consumption and data collection delay.In view of the location of mobile nodes in data collection process,in order to balance the relationship between network node energy consumption and data collection delay,a mobile data collection algorithm based on dangerous scenes is proposed in this paper.Firstly,the algorithm transforms the minimized mobile node path problem into an integer linear programming model with the optimization theory.By selecting data collection points,constructing data collection trees,and performing optimization operations on the collection tree,the load of tree root nodes is more balanced,so that the life cycle of the network will be prolonged.And it selected the docked node in the data collection process of the mobile node according to the collection point.In order to form a loop between the sink and the docked node,the data collection delay is effectively shortened.At the same time,the ant colony algorithm is used to find the TSP problem between sink and docked nodes.First,the basic principle and algorithm model of ant colony algorithm are introduced.By analyzing the shortage of ant colony algorithm in obtaining the global optimal solution,an optimized ant colony path planning algorithm is proposed.In the parameter setting of the algorithm,the chaos theory isintroduced to the adaptive adjustment of the parameters of the ant colony algorithm.A dynamic factor is introduced in terms of pheromone update rule of ant colony algorithm,so that every iteration can control the update proportion of pheromone concentration on the optimal path adaptively.Finally,through simulation and comparative analysis,it is verified that the improved ant colony algorithm can effectively improve the ant's global search ability,shorten the data collection path of mobile nodes,and meet the data collection requirements of wireless sensor network under dangerous scenes.