Deployment and Optimization of Multi-UAV-Assisted Maritime Internet of Things for Waterway Data Collection

Maritime Internet of Things (MIoT) is regarded as one of the important paradigms to realize the Smart Ocean. With the increasing number of vessels, it is significant to ensure navigation safety and prevent traffic accidents. Due to the advantages of fast mobility and flexible deployment, Unmanned Ae...

Full description

Saved in:
Bibliographic Details
Published in2021 International Conference on Security, Pattern Analysis, and Cybernetics(SPAC pp. 577 - 580
Main Authors Zhang, Yajing, Lin, Bin, Hu, Xu, Wang, Zirui
Format Conference Proceeding
LanguageEnglish
Published IEEE 18.06.2021
Subjects
Online AccessGet full text
DOI10.1109/SPAC53836.2021.9540006

Cover

More Information
Summary:Maritime Internet of Things (MIoT) is regarded as one of the important paradigms to realize the Smart Ocean. With the increasing number of vessels, it is significant to ensure navigation safety and prevent traffic accidents. Due to the advantages of fast mobility and flexible deployment, Unmanned Aerial Vehicles (UAV) can be employed to detect and collect data packets from Sensor Nodes (SNs). However, it is extreme challenging for one energy-constrained UAV to complete the data collection task while updating information in time. In this paper, we present a Multi-UA V-Assisted MioT (MUA-MIOT) architecture for collecting navigational data packets which can provide important information support for navigation safety. In addition, the optimal deployment for MUA-MIoT is investigated to achieve data packet collection and information detection. UAVis used as a data collection point to collect data packets from sensor nodes by hovering over them. The Integer Linear Programming (ILP) problem is formulated with the objective of minimizing energy consumption in the MUA-MIoT. Considering a series of constraints such as reliability and connectivity, the optimal deployment is given and then its feasibility and scalability is evaluated in simulations.
DOI:10.1109/SPAC53836.2021.9540006