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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - AoI-Minimal Trajectory Planning and Data Collection in UAV-Assisted Wireless Powered IoT Networks
AU - Hu, H.
AU - Xiong, K.
AU - Qu, G.
AU - Ni, Q.
AU - Fan, P.
AU - Letaief, K.B.
N1 - ©2021 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PY - 2021/1/15
Y1 - 2021/1/15
N2 - This article investigates the unmanned aerial vehicle (UAV)-assisted wireless powered Internet-of-Things system, where a UAV takes off from a data center, flies to each of the ground sensor nodes (SNs) in order to transfer energy and collect data from the SNs, and then returns to the data center. For such a system, an optimization problem is formulated to minimize the average Age of Information (AoI) of the data collected from all ground SNs. Since the average AoI depends on the UAV's trajectory, the time required for energy harvesting (EH) and data collection for each SN, these factors need to be optimized jointly. Moreover, instead of the traditional linear EH model, we employ a nonlinear model because the behavior of the EH circuits is nonlinear by nature. To solve this nonconvex problem, we propose to decompose it into two subproblems, i.e., a joint energy transfer and data collection time allocation problem and a UAV's trajectory planning problem. For the first subproblem, we prove that it is convex and give an optimal solution by using Karush-Kuhn-Tucker (KKT) conditions. This solution is used as the input for the second subproblem, and we solve optimally it by designing dynamic programming (DP) and ant colony (AC) heuristic algorithms. The simulation results show that the DP-based algorithm obtains the minimal average AoI of the system, and the AC-based heuristic finds solutions with near-optimal average AoI. The results also reveal that the average AoI increases as the flying altitude of the UAV increases and linearly with the size of the collected data at each ground SN.
AB - This article investigates the unmanned aerial vehicle (UAV)-assisted wireless powered Internet-of-Things system, where a UAV takes off from a data center, flies to each of the ground sensor nodes (SNs) in order to transfer energy and collect data from the SNs, and then returns to the data center. For such a system, an optimization problem is formulated to minimize the average Age of Information (AoI) of the data collected from all ground SNs. Since the average AoI depends on the UAV's trajectory, the time required for energy harvesting (EH) and data collection for each SN, these factors need to be optimized jointly. Moreover, instead of the traditional linear EH model, we employ a nonlinear model because the behavior of the EH circuits is nonlinear by nature. To solve this nonconvex problem, we propose to decompose it into two subproblems, i.e., a joint energy transfer and data collection time allocation problem and a UAV's trajectory planning problem. For the first subproblem, we prove that it is convex and give an optimal solution by using Karush-Kuhn-Tucker (KKT) conditions. This solution is used as the input for the second subproblem, and we solve optimally it by designing dynamic programming (DP) and ant colony (AC) heuristic algorithms. The simulation results show that the DP-based algorithm obtains the minimal average AoI of the system, and the AC-based heuristic finds solutions with near-optimal average AoI. The results also reveal that the average AoI increases as the flying altitude of the UAV increases and linearly with the size of the collected data at each ground SN.
KW - Age of Information (AoI)
KW - energy harvesting (EH)
KW - Internet of Things (IoT)
KW - time allocation
KW - trajectory design
KW - unmanned aerial vehicle (UAV)-assisted networks
KW - Ant colony optimization
KW - Antennas
KW - Data acquisition
KW - Dynamic programming
KW - Electronic document exchange
KW - Energy harvesting
KW - Energy transfer
KW - Heuristic algorithms
KW - Sensor nodes
KW - Trajectories
KW - Unmanned aerial vehicles (UAV)
KW - Data collection
KW - Karush-Kuhn-Tucker condition
KW - Non-linear model
KW - Nonconvex problem
KW - Optimal solutions
KW - Optimization problems
KW - Trajectory Planning
KW - Transfer energy
KW - Internet of things
U2 - 10.1109/JIOT.2020.3012835
DO - 10.1109/JIOT.2020.3012835
M3 - Journal article
VL - 8
SP - 1211
EP - 1223
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
SN - 2327-4662
IS - 2
ER -