Data Collection of IoT Devices Using an Energy-Constrained UAV

Yuchen Li, Weifa Liang, Wenzheng Xu, Xiaohua Jia

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

21 Citations (Scopus)

Abstract

In this paper, we study sensing data collection from IoT devices in a wireless 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 from IoT devices using the UAV, by finding a closed tour for the UAV that includes hovering locations and the sojourn duration at each of the hovering locations such that the accumulative volume of data collected is maximized, subject to the energy capacity on the UAV, where the UAV consumes its energy on both hovering 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 the sensory data from multiple IoT devices simultaneously if the IoT devices are within the hovering coverage range of the UAV. We then formulate two data collection maximization problems, and show that both of the problems are NP-hard. We instead devise efficient approximation and heuristic algorithms for the problems. We finally evaluate the performance of the proposed algorithms through experimental simulations. Experimental results demonstrated that the proposed algorithms are promising.
Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium, IPDPS 2020
PublisherIEEE
Pages644-653
ISBN (Print)9781728168760
DOIs
Publication statusPublished - May 2020
Event34th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2020) - Virtual, New Orleans, United States
Duration: 18 May 202022 May 2020

Publication series

NameProceedings - IEEE International Parallel and Distributed Processing Symposium, IPDPS
ISSN (Print)1530-2075

Conference

Conference34th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2020)
Country/TerritoryUnited States
CityNew Orleans
Period18/05/2022/05/20

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