Developing power control algorithms for dynamic multi-connection industrial wireless sensor networks

In this paper, we propose a Dynamic Multi-Connection Industrial Wireless Sensor Network (DMC IWSN) model to improve data transmission efficiency in a factory workshop. We introduce a new power control algorithm called Window-Selection (WS), which adjusts sensor power based on predefined upper and lower limits. The algorithm reduces power when it exceeds the upper limit, increases power when it falls below the lower limit, and maintains power within these bounds. We compare the performance of the WS algorithm with the Max-Min (MM) algorithm, and a scenario no power control in terms of the weakest sensor capacity and total capacity in uplink transmission. Simulation results show that the WS algorithm achieves the highest capacities, while the MM algorithm moderately improves system performance in the DMC IWSN model.

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Publication Details

Journal
Journal of Military Science and Technology
Published
2024-12-25
DOI
https://doi.org/10.54939/1859-1043.j.mst.100.2024.12-21
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
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article

Developing power control algorithms for dynamic multi-connection industrial wireless sensor networks

Đỗ Thành Quân, Tiến Anh Bùi
Journal of Military Science and Technology
Energy Harvesting in Wireless Networks
article

Developing power control algorithms for dynamic multi-connection industrial wireless sensor networks

Đỗ Thành Quân, Tiến Anh Bùi
article en

Abstract

In this paper, we propose a Dynamic Multi-Connection Industrial Wireless Sensor Network (DMC IWSN) model to improve data transmission efficiency in a factory workshop. We introduce a new power control algorithm called Window-Selection (WS), which adjusts sensor power based on predefined upper and lower limits. The algorithm reduces power when it exceeds the upper limit, increases power when it falls below the lower limit, and maintains power within these bounds. We compare the performance of the WS algorithm with the Max-Min (MM) algorithm, and a scenario no power control in terms of the weakest sensor capacity and total capacity in uplink transmission. Simulation results show that the WS algorithm achieves the highest capacities, while the MM algorithm moderately improves system performance in the DMC IWSN model.

Journal of Military Science and Technology
Le Quy Don Technical University (VN)
Affordable and clean energy
Openalex Percentile: Top 78%
Energy Harvesting in Wireless Networks
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