Research On Multi-objective Trajectories Scheduling For Mobile Data Collection In The Internet Of Things

The Internet of Things(IoT)is not only widely used in the smart home,smart city,Internet of vehicles,and other scenes with good infrastructure,but also has important application value in the military,safety monitoring,environmental monitoring,public facility protection,emergency rescue and disaster relief,and other infrastructure under-developed scenes.In the case of infrastructure under-developed,problems such as unreliable links,insufficient power supply,and unguaranteed timeliness are important bottlenecks restricting the development of the Internet of Things.The key to solving the above problems is the information collection strategy with high energy efficiency and high time efficiency.This thesis focuses on the collection of information collected by the Internet of Things under incomplete infrastructure scenarios,and studies the task assignment and trajectory scheduling problems in the remote wireless information transmission of sensor nodes with the objective of improving the network energy efficiency and time efficiency of information collection and energy supply.Based on the summarization of the latest research results,this thesis designed the clustering algorithm based on beamforming and mobile nodes respectively for the task assignment of sensor nodes.On this basis,the optimization model of mobile node trajectories scheduling under the off-line scheduling scene is formulated,and the heuristic trajectory scheduling algorithm is designed to solve the proposed optimization problem.Furthermore,considering the real-time trajectories scheduling problem of mobile nodes under the on-line scheduling scene,the corresponding optimization model is formulated,and the mobile nodes trajectories scheduling strategy is designed based on the cooperative enforcement game to solve the optimization problem.First,in order to solve the problem of remote transmission of monitoring information of sensor nodes in IoT under the condition that no additional devices can enter the sensing area,the beamforming technology in array signal processing is transplanted to the Internet of Things in this thesis,and the remote transmission of monitoring information is completed by using the clustering cooperation of sensor nodes.In order to realize the clustering cooperation of sensor nodes and reduce the energy consumption of sensor nodes,a clustering algorithm based on the sensor nodes beamforming is designed,and the number of sensor nodes and range of cluster are strictly constrained.In addition,in the scene where additional devices,such as robots,vehicles,UAVs,and other mobile nodes,can enter the sensing area,a clustering algorithm based on the energy consumption rate of sensor nodes is designed to optimize the task assignment and make the energy of sensor nodes can be timely and reasonably supplied.The advantages of these two algorithms are verified from the aspects of the success rate of clustering and the charging latency of sensor nodes in different scenes,respectively.Second,the trajectory scheduling problem of mobile nodes is studied for the off-line scheduling scene in which mobile nodes can predict network topology,energy consumption rate,and other network information.On the basis of the network model,energy consumption model,number of mobile nodes constraint model,and network energy neutral condition,the trajectory scheduling problem of minimizing the total travel distance of mobile nodes is formulated as a mixed-integer programming problem.Considering that the mathematical problem described by this optimization problem is NP-hard,heuristic trajectories scheduling algorithm for data collection is designed by means of wireless information transmission technology and wireless charging technology.Three steps of network hierarchy,clustering,and trajectories planning are designed based on the neighbor nodes to optimize the task assignment,meeting points,and trajectories of mobile nodes.Finally,the simulation results comprehensively demonstrate the performance of the proposed heuristic trajectories scheduling algorithm for mobile data collection from the aspects of travel distance,data collection latency,visit rate,and so forth.Finally,if the mobile nodes can enter the sensing area and under the condition of the on-line scheduling scene,namely mobile nodes cannot predict network topology,the energy consumption rate and other information of the network,the trajectories of mobile nodes cannot be scheduled ahead.In view of this scene,according to the received request information and the demands of sensor nodes,the mobile nodes scheduling strategy of the real-time scheduling problem is studied.On the basis of the network model,AoI model,and game model,under the constricts of the network energy-neutral conditions,the mobile nodes trajectories scheduling problem is formulated to minimize AoI and maximize the energy efficiency,which is a multi-objective programming problem.In order to solve the problem,a cooperation enforcement game strategy between mobile nodes is proposed.By using this strategy,the real-time task assignment and trajectory scheduling among mobile nodes are optimized.The advantages of the proposed mobile node trajectories scheduling algorithm are verified through the average AoI,energy efficiency,and successful visit rate.