TY - JOUR
T1 - Data Collection Maximization in IoT-Sensor Networks via an Energy-Constrained UAV
AU - Li, Yuchen
AU - Liang, Weifa
AU - Xu, Wenzheng
AU - Xu, Zichuan
AU - Jia, Xiaohua
AU - Xu, Yinlong
AU - Kan, Haibin
N1 - Publisher Copyright:
© 2002-2012 IEEE.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - In this paper, we study sensing data collection of IoT devices in a sparse IoT-sensor network, using an energy-constrained Unmanned Aerial Vehicle (UAV), where the sensory data is stored in IoT devices while the IoT devices may or may not be within the transmission range of each other. We formulate two novel data collection problems to fully or partially collect data stored from IoT devices using the UAV, by finding a closed tour for the UAV that consists of hovering locations and the sojourn duration at each of the hovering locations such that the accumulative volume of data collected within the tour is maximized, subject to the energy capacity on the UAV, where the UAV consumes energy on both hovering for data collection and flying from one hovering location to another hovering location. To this end, we first propose a novel data collection framework that enables the UAV to collect sensory data from multiple IoT devices simultaneously if these IoT devices are within the coverage range of the UAV, through adopting the orthogonal frequency division multiple access (OFDMA) technique. We then formulate two data collection maximization problems to deal with full or partial data collection from IoT devices at each hovering location, and show that both defined problems are NP-hard. We instead devise approximation and heuristic algorithms for the problems. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrated that the proposed algorithms are promising.
AB - In this paper, we study sensing data collection of IoT devices in a sparse IoT-sensor network, using an energy-constrained Unmanned Aerial Vehicle (UAV), where the sensory data is stored in IoT devices while the IoT devices may or may not be within the transmission range of each other. We formulate two novel data collection problems to fully or partially collect data stored from IoT devices using the UAV, by finding a closed tour for the UAV that consists of hovering locations and the sojourn duration at each of the hovering locations such that the accumulative volume of data collected within the tour is maximized, subject to the energy capacity on the UAV, where the UAV consumes energy on both hovering for data collection and flying from one hovering location to another hovering location. To this end, we first propose a novel data collection framework that enables the UAV to collect sensory data from multiple IoT devices simultaneously if these IoT devices are within the coverage range of the UAV, through adopting the orthogonal frequency division multiple access (OFDMA) technique. We then formulate two data collection maximization problems to deal with full or partial data collection from IoT devices at each hovering location, and show that both defined problems are NP-hard. We instead devise approximation and heuristic algorithms for the problems. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrated that the proposed algorithms are promising.
KW - IoT applications
KW - UAV trajectory finding
KW - Wireless sensor networks
KW - a single UAV
KW - approximation algorithms
KW - collecting data from multiple sensors simultaneously
KW - energy-constrained optimization
KW - full and partial data collection
KW - the orienteering problem
UR - http://www.scopus.com/inward/record.url?scp=85107364832&partnerID=8YFLogxK
U2 - 10.1109/TMC.2021.3084972
DO - 10.1109/TMC.2021.3084972
M3 - Article
SN - 1536-1233
VL - 22
SP - 159
EP - 174
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 1
ER -