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

Van Vi Vo; Phuoc Nguyen Bui; Duc Tai Le; Hyunseung Choo

doi:10.1007/978-981-19-8069-5_47

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

Van Vi Vo, Phuoc Nguyen Bui, Duc Tai Le, Hyunseung Choo

Department of Computer Science and Engineering

Sungkyunkwan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications - 9th International Conference, FDSE 2022, Proceedings
Editors	Tran Khanh Dang, Josef Küng, Tai M. Chung
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	674-681
Number of pages	8
ISBN (Print)	9789811980688
DOIs	https://doi.org/10.1007/978-981-19-8069-5_47
State	Published - 2022
Event	9th International Conference on Future Data and Security Engineering, FDSE 2022 - Ho Chi Minh City, Viet Nam Duration: 23 Nov 2022 → 25 Nov 2022

Publication series

Name	Communications in Computer and Information Science
Volume	1688 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	9th International Conference on Future Data and Security Engineering, FDSE 2022
Country/Territory	Viet Nam
City	Ho Chi Minh City
Period	23/11/22 → 25/11/22

Keywords

Battery-free
Data aggregation
Energy harvesting
Internet of things
Wireless sensor network

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-981-19-8069-5_47

Cite this

Vo, V. V., Bui, P. N., Le, D. T., & Choo, H. (2022). Energy Harvesting Aware for Delay-Efficient Data Aggregation in Battery-Free IoT Sensors. In T. K. Dang, J. Küng, & T. M. Chung (Eds.), Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications - 9th International Conference, FDSE 2022, Proceedings (pp. 674-681). (Communications in Computer and Information Science; Vol. 1688 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-8069-5_47

Vo, Van Vi ; Bui, Phuoc Nguyen ; Le, Duc Tai et al. / Energy Harvesting Aware for Delay-Efficient Data Aggregation in Battery-Free IoT Sensors. Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications - 9th International Conference, FDSE 2022, Proceedings. editor / Tran Khanh Dang ; Josef Küng ; Tai M. Chung. Springer Science and Business Media Deutschland GmbH, 2022. pp. 674-681 (Communications in Computer and Information Science).

@inproceedings{75ac862c5b9c49bc8150d58b45921cd6,

title = "Energy Harvesting Aware for Delay-Efficient Data Aggregation in Battery-Free IoT Sensors",

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.",

keywords = "Battery-free, Data aggregation, Energy harvesting, Internet of things, Wireless sensor network",

author = "Vo, \{Van Vi\} and Bui, \{Phuoc Nguyen\} and Le, \{Duc Tai\} and Hyunseung Choo",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 9th International Conference on Future Data and Security Engineering, FDSE 2022 ; Conference date: 23-11-2022 Through 25-11-2022",

year = "2022",

doi = "10.1007/978-981-19-8069-5\_47",

language = "English",

isbn = "9789811980688",

series = "Communications in Computer and Information Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "674--681",

editor = "Dang, \{Tran Khanh\} and Josef K{\"u}ng and Chung, \{Tai M.\}",

booktitle = "Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications - 9th International Conference, FDSE 2022, Proceedings",

}

Vo, VV, Bui, PN, Le, DT & Choo, H 2022, Energy Harvesting Aware for Delay-Efficient Data Aggregation in Battery-Free IoT Sensors. in TK Dang, J Küng & TM Chung (eds), Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications - 9th International Conference, FDSE 2022, Proceedings. Communications in Computer and Information Science, vol. 1688 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 674-681, 9th International Conference on Future Data and Security Engineering, FDSE 2022, Ho Chi Minh City, Viet Nam, 23/11/22. https://doi.org/10.1007/978-981-19-8069-5_47

Energy Harvesting Aware for Delay-Efficient Data Aggregation in Battery-Free IoT Sensors. / Vo, Van Vi; Bui, Phuoc Nguyen; Le, Duc Tai et al.
Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications - 9th International Conference, FDSE 2022, Proceedings. ed. / Tran Khanh Dang; Josef Küng; Tai M. Chung. Springer Science and Business Media Deutschland GmbH, 2022. p. 674-681 (Communications in Computer and Information Science; Vol. 1688 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Energy Harvesting Aware for Delay-Efficient Data Aggregation in Battery-Free IoT Sensors

AU - Vo, Van Vi

AU - Bui, Phuoc Nguyen

AU - Le, Duc Tai

AU - Choo, Hyunseung

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Battery-free

KW - Data aggregation

KW - Energy harvesting

KW - Internet of things

KW - Wireless sensor network

UR - https://www.scopus.com/pages/publications/85145006328

U2 - 10.1007/978-981-19-8069-5_47

DO - 10.1007/978-981-19-8069-5_47

M3 - Conference contribution

AN - SCOPUS:85145006328

SN - 9789811980688

T3 - Communications in Computer and Information Science

SP - 674

EP - 681

BT - Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications - 9th International Conference, FDSE 2022, Proceedings

A2 - Dang, Tran Khanh

A2 - Küng, Josef

A2 - Chung, Tai M.

PB - Springer Science and Business Media Deutschland GmbH

T2 - 9th International Conference on Future Data and Security Engineering, FDSE 2022

Y2 - 23 November 2022 through 25 November 2022

ER -

Vo VV, Bui PN, Le DT, Choo H. Energy Harvesting Aware for Delay-Efficient Data Aggregation in Battery-Free IoT Sensors. In Dang TK, Küng J, Chung TM, editors, Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications - 9th International Conference, FDSE 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 674-681. (Communications in Computer and Information Science). doi: 10.1007/978-981-19-8069-5_47