Data Collection Maximization in IoT-Sensor Networks Via an Energy-Constrained UAV

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

1 Scopus Citations
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Author(s)

  • Yuchen Li
  • Wenzheng Xu
  • Zichuan Xu
  • Yinlong Xu
  • Haibin Kan

Related Research Unit(s)

Detail(s)

Original languageEnglish
Number of pages16
Journal / PublicationIEEE Transactions on Mobile Computing
Publication statusOnline published - 31 May 2021

Abstract

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 such that the accumulative volume of data collected within the tour is maximized, subject to the energy capacity on the UAV. 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 the IoT devices are within the coverage range of the UAV. We then formulate two data collection maximization problems to deal with full or partial data collection from sensors and show that both problems are NP-hard. We instead devise approximation and heuristic algorithms for them. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrated that the proposed algorithms are promising.

Research Area(s)

  • a single UAV, Aggregates, approximation algorithms, collecting data from multiple sensors simultaneously, Data collection, energy-constrained optimization, full and partial data collection, Heuristic algorithms, Internet of Things, IoT applications, the orienteering problem, Trajectory, UAV trajectory finding, Unmanned aerial vehicles, Wireless sensor networks