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Sensors and Materials, Volume 33, Number 5(2) (2021)
Copyright(C) MYU K.K.
pp. 1551-1564
S&M2554 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2021.3041
Published: May 12, 2021

Wireless Body Area Network Auxiliary Relief Mechanism Based on Uneven Population Clustering and Rescue Request Information Diffusion Strategy [PDF]

Fenglian Jiang, Mingling Wang, Chun-Chi Chen, and Hsien-Wei Tseng

(Received July 20, 2020; Accepted March 17, 2021)

Keywords: wireless body area network, relief mechanism, uneven clustering, propagation strategy, energy consumption balance, network dynamics

We propose an auxiliary relief mechanism (ARM) for a wireless body area network (WBAN). The ARM, as a supplement to the traditional medical assistance provided by a WBAN, aims at solving the problem of the lack of timely relief in the existing WBAN relief mechanism. When an emergency occurs, it can help RSs find k potential rescuers (PRs) nearby. By fully considering the limited energy consumption and dynamic characteristic of auxiliary relief network (ARN) nodes, we propose an ARN dynamic population clustering algorithm for the ARM to cluster people around RSs, which uses dynamic uneven clustering to ensure balanced energy consumption between clusters. On the basis of the clustering, a rescue request information (RRI) diffusion strategy is proposed, and appropriate intracluster and intercluster propagation strategies are adopted to spread the RRI, so that the information can be transmitted quickly to k PRs. Our experiment shows that the ARN dynamic population clustering algorithm realizes uneven clustering for a dynamic population. The ARM RRI diffusion strategy is superior to a comparative algorithm in both searching time and energy consumption, and has higher searching efficiency.

Corresponding author: Chun-Chi Chen, Hsien-Wei Tseng


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Cite this article
Fenglian Jiang, Mingling Wang, Chun-Chi Chen, and Hsien-Wei Tseng, Wireless Body Area Network Auxiliary Relief Mechanism Based on Uneven Population Clustering and Rescue Request Information Diffusion Strategy, Sens. Mater., Vol. 33, No. 5, 2021, p. 1551-1564.



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