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Energy-Efficient Access Point Deployment for Industrial IoT Systems

Published

Author(s)

Xiaowen Qi, Jing Geng, Mohamed Hany, Shuvra Bhattacharyya, Rick Candell

Abstract

Internet of Things (IoT) technologies have impacted many fields by opening up much deeper and more extensive integration of communications connectivity, sensing, and embedded processing. The industrial sector is among the areas that have been impacted greatly — for example, IoT has the potential to provide novel capabilities for more effective tracking, control and optimization of industrial processes. To maintain reliable embedded processing and connectivity in industrial IoT (IIoT) systems, including systems that involve intensive use of smart wearable technologies, energy consumption is often a critical consideration. With this motivation, this paper develops an energy-efficient deployment strategy for access points in IIoT systems. The developed strategy is based on a novel genetic algorithm called the Access Point Placement Genetic Algorithm (AP2GA). Simulation results with our proposed deployment strategy demonstrate the effectiveness of AP2GA in optimizing energy consumption for IIoT systems.
Proceedings Title
6TH IFIP INTERNATIONAL INTERNET OF THINGS (IoT) CONFERENCE
Volume
638
Conference Dates
November 2-3, 2023
Conference Location
Denton, TX, US

Keywords

Green Communication , Wireless Industrial IoT , Genetic Algorithm

Citation

Qi, X. , Geng, J. , Hany, M. , Bhattacharyya, S. and Candell, R. (2023), Energy-Efficient Access Point Deployment for Industrial IoT Systems, 6TH IFIP INTERNATIONAL INTERNET OF THINGS (IoT) CONFERENCE, Denton, TX, US, [online], https://doi.org/10.1007/978-3-031-45878-1_13, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956449 (Accessed June 16, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created October 26, 2023, Updated December 27, 2023