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Cited by 3Wireless Body Area NetworksEnergy Efficient Wireless Sensor NetworksMolecular Communication and Nanonetworks

Energy-Efficient Algorithms and Protocols for Wireless Body Sensor Networks

Zhang, Rongrong, Yu, Jihong·2020·Springer eBooks
DOI 10.1007/978-3-030-28580-7
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  • Energy-efficient routing algorithms leverage reinforcement learning to adaptively optimize network pathways based on real-time energy constraints.

    “energy-efficient routing algorithms leverage reinforcement learning to adaptively optimize network pathways based on real-time energy constraints [28].”

    From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [28]

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Authors
Zhang, R., & Yu, J.
Affiliations
  • Capital Normal University (CN)
  • Beijing Institute of Technology (CN)
ORCID
Venue
Springer eBooks
Publisher
Springer International Publishing
Published
2020
DOI
10.1007/978-3-030-28580-7
OpenAlex
W2970126520
Cited by
3
References
0
Citations by year
2024: 1 · 2023: 1 · 2021: 1
FWCI
0.15
Type
book
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)
Locations
  • Springer eBooks (publishedVersion)
  • International Linear Collider (submittedVersion)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
  • Physical Sciences › Computer Science › Computer Networks and Communications › Energy Efficient Wireless Sensor Networks
  • Physical Sciences › Engineering › Biomedical Engineering › Molecular Communication and Nanonetworks
Keywords
wireless body sensor networks, energy efficiency, energy-efficient algorithms, energy-efficient protocols, algorithm design, optimization, theoretical modeling

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