AoI-Sensitive Data Collection in Multi-UAV-Assisted Wireless Sensor Networks
The unmanned aerial vehicle (UAV) is widely used in some scenes with high requirements for information freshness. Due to the limited endurance of the UAV, especially in the scenes with large area and dense sensor nodes (SNs), it is difficult for one UAV to complete the data collection task under the...
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| Vydáno v: | IEEE transactions on wireless communications Ročník 22; číslo 8; s. 5185 - 5197 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
IEEE
01.08.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1536-1276, 1558-2248 |
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| Abstract | The unmanned aerial vehicle (UAV) is widely used in some scenes with high requirements for information freshness. Due to the limited endurance of the UAV, especially in the scenes with large area and dense sensor nodes (SNs), it is difficult for one UAV to complete the data collection task under the condition of ensuring the freshness of SNs' information. Therefore, multiple UAVs are required to cooperate to participate in data collection. In this paper, we study the multi-UAV assisted data collection problem to improve information freshness. We use the Age of Information (AoI) to measure the freshness of information, mainly including the SNs' uploading time, the UAVs' flight time and the data offloading time. The data collection problem is formulated to minimize the SNs' peak AoI and average AoI in multi-UAV assisted wireless sensor networks. Since the problem is complex, we introduce a start-to-end strategy comprising of association and planning to minimize two SNs' AoIs through an iterative three-step process. Firstly, the locations of data collection points (CPs) at which the UAVs hover to collect data and the SN-CP association are determined based on a density-based clustering algorithm. Secondly, the CPs are clustered to form CP clusters, and the CP-UAV association is established. Finally, based on the results of the above two steps, the flight trajectories of the UAVs are optimized by improved ant colony (ACO) algorithm subject to the limited endurance capability. The simulation results show the proposed strategy can optimize the peak-AoI and ave-AoI of SNs to improve the freshness of information. |
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| AbstractList | The unmanned aerial vehicle (UAV) is widely used in some scenes with high requirements for information freshness. Due to the limited endurance of the UAV, especially in the scenes with large area and dense sensor nodes (SNs), it is difficult for one UAV to complete the data collection task under the condition of ensuring the freshness of SNs’ information. Therefore, multiple UAVs are required to cooperate to participate in data collection. In this paper, we study the multi-UAV assisted data collection problem to improve information freshness. We use the Age of Information (AoI) to measure the freshness of information, mainly including the SNs’ uploading time, the UAVs’ flight time and the data offloading time. The data collection problem is formulated to minimize the SNs’ peak AoI and average AoI in multi-UAV assisted wireless sensor networks. Since the problem is complex, we introduce a start-to-end strategy comprising of association and planning to minimize two SNs’ AoIs through an iterative three-step process. Firstly, the locations of data collection points (CPs) at which the UAVs hover to collect data and the SN-CP association are determined based on a density-based clustering algorithm. Secondly, the CPs are clustered to form CP clusters, and the CP-UAV association is established. Finally, based on the results of the above two steps, the flight trajectories of the UAVs are optimized by improved ant colony (ACO) algorithm subject to the limited endurance capability. The simulation results show the proposed strategy can optimize the peak-AoI and ave-AoI of SNs to improve the freshness of information. |
| Author | Gao, Xingxia Zhu, Xiumin Zhai, Linbo |
| Author_xml | – sequence: 1 givenname: Xingxia orcidid: 0000-0001-5627-5618 surname: Gao fullname: Gao, Xingxia email: 2021020960@stu.sdnu.edu.cn organization: School of Information Science and Engineering, Shandong Normal University, Jinan, China – sequence: 2 givenname: Xiumin orcidid: 0000-0001-5947-0021 surname: Zhu fullname: Zhu, Xiumin email: 2020020895@stu.sdnu.edu.cn organization: School of Information Science and Engineering, Shandong Normal University, Jinan, China – sequence: 3 givenname: Linbo orcidid: 0000-0002-5064-0255 surname: Zhai fullname: Zhai, Linbo email: zhai@mail.sdu.edu.cn organization: School of Information Science and Engineering, Shandong Normal University, Jinan, China |
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| SubjectTerms | Age of information Algorithms Ant colony optimization Autonomous aerial vehicles Big Data Clustering Clustering algorithms Data collection data collection points Energy consumption Flight time Freshness improved ACO multi-UAV Sensors Strategy Trajectory Unmanned aerial vehicles Wireless communication Wireless sensor networks |
| Title | AoI-Sensitive Data Collection in Multi-UAV-Assisted Wireless Sensor Networks |
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