Energy-Efficient Scheduling in UAV-Assisted Hierarchical Wireless Sensor Networks

Document Type

Article

Publication Date

6-1-2024

Abstract

In emerging applications of the Internet of Things, wireless sensor networks (WSNs) are often utilized to gather, track, and monitor data in remote areas with limited communication infrastructure. Since the majority of WSNs employ sensors powered by batteries, maintaining energy efficiency, and conservation is crucial for ensuring their sustained operations over time. This work designs an Energy-efficient unmanned aerial vehicle (UAV)-assisted hierarchical architecture of WSNs (EUW). EUW supports fast transmission of data collected from WSNs to a cloud server. Based on this architecture, this work first formulates a joint optimization problem for cluster head selection, time slot allocation, and UAV path planning to minimize the weighted sum of energy consumption of WSNs and that of a UAV. Then, a hybrid meta-heuristic algorithm named knowledge transfer-based particle swarm optimization (KTPSO) is designed, which utilizes previous optimization results to increase the convergence speed and find better results. Finally, numerical analysis and evaluation results are shown to demonstrate the efficiency of KTPSO and the proposed UAV-assisted architecture of hierarchical WSNs.

Identifier

85186974369 (Scopus)

Publication Title

IEEE Internet of Things Journal

External Full Text Location

https://doi.org/10.1109/JIOT.2024.3369722

e-ISSN

23274662

First Page

20194

Last Page

20206

Issue

11

Volume

11

Grant

62173013

Fund Ref

National Natural Science Foundation of China

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