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Energy Harvesting Aware for Delay-Efficient Data Aggregation in Battery-Free IoT Sensors

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Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications (FDSE 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1688))

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Abstract

Battery-Free Wireless Sensor Network (BF-WSN) is a new energy harvesting technology that has been successfully integrated into Wireless Sensor Networks (WSNs). It allows sensor batteries to be charged using renewable energy sources. Sensor nodes in BF-WSNs are no longer constrained by the equipped batteries, but rather by the amount of energy harvested from their surroundings. In sensor networks, data aggregation is a fundamental procedure in which sensory data collected by relay nodes is merged using in-network computation. The Minimum Latency Aggregation Scheduling (MLAS) problem, which has been widely studied in battery-powered WSNs, is always a critical issue in WSNs. Modern approaches used in battery-powered WSNs, on the other hand, are incompatible with the use of BF-WSNs due to the limited energy harvesting capabilities of battery-free sensor nodes. In this paper, we investigate the MLAS problem in BF-WSNs. Leveraging the energy harvesting ability of the battery-free sensor nodes, we propose an approach that assigns more senders to relay nodes having high energy harvesting rates and schedules nodes whenever are ready for energy capacity data transmissions. Through extensive simulations, our proposed scheme surpasses the modern approach at most 40% in terms of aggregation delay.

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Acknowledgement

This work is supported by the Ministry of Education Korea (NRF-2020 R1A2C2008447) and by IITP grant funded by the Korea government (MSIT) under the ICT Creative Consilience program (IITP-2022-2020-0-0182) and Artificial Intelligence Innovation Hub (No.2021-0-02068).

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, South Korea

    Van-Vi Vo & Hyunseung Choo

  2. Department of Superintelligence Engineering, Sungkyunkwan University, Suwon, South Korea

    Phuoc-Nguyen Bui

  3. College of Computing and Informatics, Sungkyunkwan University, Suwon, South Korea

    Duc-Tai Le

Authors
  1. Van-Vi Vo
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  2. Phuoc-Nguyen Bui
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  3. Duc-Tai Le
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  4. Hyunseung Choo
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Corresponding author

Correspondence to Hyunseung Choo .

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Editors and Affiliations

  1. Ho Chi Minh City University of Food Industry, Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler University of Linz, Linz, Austria

    Josef Küng

  3. Sungkyunkwan University, Seoul, Korea (Republic of)

    Tai M. Chung

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Vo, VV., Bui, PN., Le, DT., Choo, H. (2022). Energy Harvesting Aware for Delay-Efficient Data Aggregation in Battery-Free IoT Sensors. In: Dang, T.K., Küng, J., Chung, T.M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2022. Communications in Computer and Information Science, vol 1688. Springer, Singapore. https://doi.org/10.1007/978-981-19-8069-5_47

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  • DOI: https://doi.org/10.1007/978-981-19-8069-5_47

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-8068-8

  • Online ISBN: 978-981-19-8069-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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