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

Rui Lai, Boyuan Zhang, Guanghong Gong, Haitao Yuan, Jinhong Yang, Jia Zhang, Mengchu Zhou

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)20194-20206
Number of pages13
JournalIEEE Internet of Things Journal
Volume11
Issue number11
DOIs
StatePublished - Jun 1 2024

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Science Applications

Keywords

  • Cluster head (CH) selection
  • hybrid meta-heuristic algorithms
  • time slot allocation (TSA)
  • unmanned aerial vehicle (UAV) path planning
  • wireless sensor networks (WSNs)

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