Balanced Space- and Time-based Duty-cycle Scheduling for Light-based IoT

In this work, we propose a Multiple Access Control (MAC) protocol for Light-based IoT (LIoT) networks, where the gateway node orchestrates and schedules batteryless nodes' duty-cycles based on their location and sleep time.The LIoT concept represents a sustainable solution for massive indoor IoT applications, offering an alternative communication medium through Visible Light Communication (VLC).While most existing scheduling algorithms for intermittent batteryless IoT aim to maximize data collection and enhance dataset size, our solution is tailored for environmental sensing applications, such as temperature, humidity, and air quality monitoring, optimizing measurement distribution and minimizing blind spots to achieve comprehensive and uniform environmental sensing.We propose a Balanced Space and Time-based Time Division Multiple Access scheduling (BST-TDMA) algorithm, which addresses environmental sensing challenges by balancing spatial and temporal factors to improve the environmental sensing efficiency of batteryless LIoT nodes.Our measurement-based results show that BST-TDMA was able to efficiently schedule duty-cycles with given intervals.

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Publication Details

Published
2024-11-19
DOI
https://doi.org/10.1145/3703790.3703827
Citations
3
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
1.05

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article

Balanced Space- and Time-based Duty-cycle Scheduling for Light-based IoT

Sofie Pollin, Khojiakbar Botirov, Hazem Sallouha, Marcos Katz
3 citations
IoT and Edge/Fog Computing
1.05
article

Balanced Space- and Time-based Duty-cycle Scheduling for Light-based IoT

Sofie Pollin, Khojiakbar Botirov, Hazem Sallouha, Marcos Katz
article en
3 citations

Abstract

In this work, we propose a Multiple Access Control (MAC) protocol for Light-based IoT (LIoT) networks, where the gateway node orchestrates and schedules batteryless nodes' duty-cycles based on their location and sleep time.The LIoT concept represents a sustainable solution for massive indoor IoT applications, offering an alternative communication medium through Visible Light Communication (VLC).While most existing scheduling algorithms for intermittent batteryless IoT aim to maximize data collection and enhance dataset size, our solution is tailored for environmental sensing applications, such as temperature, humidity, and air quality monitoring, optimizing measurement distribution and minimizing blind spots to achieve comprehensive and uniform environmental sensing.We propose a Balanced Space and Time-based Time Division Multiple Access scheduling (BST-TDMA) algorithm, which addresses environmental sensing challenges by balancing spatial and temporal factors to improve the environmental sensing efficiency of batteryless LIoT nodes.Our measurement-based results show that BST-TDMA was able to efficiently schedule duty-cycles with given intervals.

University of Oulu (FI), KU Leuven (BE)
European Commission, Fonds Wetenschappelijk Onderzoek, Vlaamse regering
Affordable and clean energy
Openalex Percentile: Top 20%
IoT and Edge/Fog Computing
1.05
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