Research On UAV-aided Data Collection Mechanism Based On 60 GHz Communication

In recent years,the Internet of Things(IoT)technology has developed rapidly and has been widely applied in various applications such as smart cities,smart agriculture,and smart industries.As an important research field of IoT,data collection has attracted more and more attention.In some linear scenarios such as roads,bridges,rivers,and pipelines,cameras are usually deployed for video surveillance to achieve safety prevention or environmental monitoring.As a kind of data-intensive IoT devices,high-definition cameras often use wired communication for high-speed transmission of video data.When the wired network infrastructures are inadequate or destroyed,or when temporary monitoring is required,the wireless transmission plays an important role.However,existing solutions usually adopt traditional wireless communication technologies to achieve low-bandwidth data connections between IoT devices.The transmission rates and energy efficiency of them are low,and the deployment of devices is limited by the communication distance.Therefore,how to provide efficient wireless data collection of data-intensive IoT nodes in linear scenarios is an urgent problem to be solved.To this end,this thesis adopts the 60 GHz communication technology to provide highbandwidth wireless transmission for data-intensive IoT devices.However,60 GHz links are subject to line-of-sight short communication range,therefore,this thesis uses unmanned aerial vehicles(UAV)to achieve short-range high-throughput 60 GHz transmission and studies UAVassisted data collection based on 60 GHz communication.Considering that the UAV is powered by onboard batteries and has limited energy,this thesis proposes an energy-efficient UAV scheduling algorithm.What’s more,considering the demand for data freshness in delaysensitive applications,this thesis introduces the age of information(AoI)as a metric and proposes a low AoI UAV scheduling algorithm.Specific research results include:Firstly,an energy-efficient UAV scheduling mechanism that meets the global data collection requirements is investigated and designed.For data collection scenarios where dataintensive IoT devices are deployed linearly,this thesis plans to minimize the UAV flights in the limitations of the UAV’s energy and storage capacity.First,this thesis studies the singledirection problem where the starting point of the UAV is located at one end of the scenario,and proposes the NF＿SUFS algorithm and the FF＿SUFS algorithm whose approximation ratio is proved to be 2.Then,considering a general case where the starting point is located anywhere in the scenario,the FF＿UFS algorithm is proposed,and its approximation ratio is proved to be3.Finally,the effectiveness and efficiency of the proposed algorithms and the correctness of the theoretical approximation ratio are verified by simulation experiments.Secondly,a low-AoI UAV scheduling mechanism that adapts to frequent data updates is investigated and designed.For the frequent data update scenarios in the linear scenario,this thesis considers the need for data timeliness and plans to minimize the average accumulated AoI in the limitations of UAV’s energy and storage capacity.The semi-Markov decision process is used to model the multi-UAV cooperative scheduling problem in linear scenarios.In order to solve this problem,this thesis proposes the CoS-OD algorithm which uses the optionbased reinforcement method and combines with greedy strategy to guide multi-UAV cooperation in target selection and reduce the AoI.Finally,the effectiveness and efficiency of the algorithm are verified through simulation experiments.Thirdly,a prototype system of UAV-aided data collection based on 60 GHz communication is designed and implemented based on the above research results.What’s more,the usability and effectiveness of the prototype system are verified through tests.To sum up,this thesis has conducted an in-depth exploration of the UAV-aided data collection mechanism based on 60 GHz communication in linear scenarios.The experiments show that the algorithms proposed in this paper can reasonably utilize the high throughput of60 GHz communication and optimize the energy consumption of UAVs to provide energyefficient and low AoI data collection.The research work in this thesis provides the theoretical basis and technical support for data collection of data-intensive IoT devices.