Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system
A rechargeable unmanned aerial vehicle (UAV) aided wireless sensor network was considered, which consists of multiple ground terminals with a large amount of time-sensitive data to be collected.Due to the limited battery capacity, the UAV cannot collect the data from all terminals through a single f...
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China InfoCom Media Group
2022-09-01
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| Series: | 物联网学报 |
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| Online Access: | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2022.00285/ |
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| author | Qianwen LI Jianfeng CHEN Miao CUI Guangchi ZHANG |
| author_facet | Qianwen LI Jianfeng CHEN Miao CUI Guangchi ZHANG |
| author_sort | Qianwen LI |
| collection | DOAJ |
| description | A rechargeable unmanned aerial vehicle (UAV) aided wireless sensor network was considered, which consists of multiple ground terminals with a large amount of time-sensitive data to be collected.Due to the limited battery capacity, the UAV cannot collect the data from all terminals through a single flight mission, and it needs to return to the charging pile to replenish its flight energy several times during the whole mission.The optimization of the terminal scheduling, trajectory, flight speed and transmission rate for the UAV was studied to maximize the number of terminals whose data had been collected within the data lifetime limit.Due to the variable coupling and the existence of discrete binary scheduling variables, the considered optimization problem is difficult to solve.To tackle such a difficulty, an efficient algorithm was proposed based on the stochastic optimization and the feature engineering.Specifically, the flight hover communication protocol was introduced to simplify the UAV flight process.And then a terminal scheduling algorithm was innovatively proposed with the influence factor and the stochastic preference, which extracted the features that affect the service time of the UAV, optimized the weights of the features, and further simplified the optimization problem into multiple subproblems.The subproblems were then solved by using the block coordinate descent and successive convex approximation techniques.Simulation results show that the proposed optimization algorithm achieves significant performance gains over several benchmark schemes in the scenarios with different data lifetime requirements and different numbers of ground terminals. |
| format | Article |
| id | doaj-art-3deafb4ab89044dba53d96483c080ef9 |
| institution | Kabale University |
| issn | 2096-3750 |
| language | zho |
| publishDate | 2022-09-01 |
| publisher | China InfoCom Media Group |
| record_format | Article |
| series | 物联网学报 |
| spelling | doaj-art-3deafb4ab89044dba53d96483c080ef92025-01-15T02:53:48ZzhoChina InfoCom Media Group物联网学报2096-37502022-09-01611312359651101Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection systemQianwen LIJianfeng CHENMiao CUIGuangchi ZHANGA rechargeable unmanned aerial vehicle (UAV) aided wireless sensor network was considered, which consists of multiple ground terminals with a large amount of time-sensitive data to be collected.Due to the limited battery capacity, the UAV cannot collect the data from all terminals through a single flight mission, and it needs to return to the charging pile to replenish its flight energy several times during the whole mission.The optimization of the terminal scheduling, trajectory, flight speed and transmission rate for the UAV was studied to maximize the number of terminals whose data had been collected within the data lifetime limit.Due to the variable coupling and the existence of discrete binary scheduling variables, the considered optimization problem is difficult to solve.To tackle such a difficulty, an efficient algorithm was proposed based on the stochastic optimization and the feature engineering.Specifically, the flight hover communication protocol was introduced to simplify the UAV flight process.And then a terminal scheduling algorithm was innovatively proposed with the influence factor and the stochastic preference, which extracted the features that affect the service time of the UAV, optimized the weights of the features, and further simplified the optimization problem into multiple subproblems.The subproblems were then solved by using the block coordinate descent and successive convex approximation techniques.Simulation results show that the proposed optimization algorithm achieves significant performance gains over several benchmark schemes in the scenarios with different data lifetime requirements and different numbers of ground terminals.http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2022.00285/rechargeable unmanned aerial vehiclesdata collectiondata lifetimeterminal schedulingrandom optimization |
| spellingShingle | Qianwen LI Jianfeng CHEN Miao CUI Guangchi ZHANG Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system 物联网学报 rechargeable unmanned aerial vehicles data collection data lifetime terminal scheduling random optimization |
| title | Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system |
| title_full | Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system |
| title_fullStr | Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system |
| title_full_unstemmed | Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system |
| title_short | Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system |
| title_sort | trajectory and communication scheduling optimization for the rechargeable uav aided data collection system |
| topic | rechargeable unmanned aerial vehicles data collection data lifetime terminal scheduling random optimization |
| url | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2022.00285/ |
| work_keys_str_mv | AT qianwenli trajectoryandcommunicationschedulingoptimizationfortherechargeableuavaideddatacollectionsystem AT jianfengchen trajectoryandcommunicationschedulingoptimizationfortherechargeableuavaideddatacollectionsystem AT miaocui trajectoryandcommunicationschedulingoptimizationfortherechargeableuavaideddatacollectionsystem AT guangchizhang trajectoryandcommunicationschedulingoptimizationfortherechargeableuavaideddatacollectionsystem |