Open Access

ARTICLE

Reliable Data Collection Model and Transmission Framework in Large-Scale Wireless Medical Sensor Networks

by Haosong Gou¹, Gaoyi Zhang¹, Renê Ripardo Calixto², Senthil Kumar Jagatheesaperumal³, Victor Hugo C. de Albuquerque^2,*

1China Mobile Group Sichuan Co., Ltd., Chengdu, 640041, China
2 Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, 60455-970, Brazil
3 Department of Electronics & Communication Engineering, Mepco Schlenk Engineering College, Sivakasi, 626005, India

* Corresponding Author: Victor Hugo C. de Albuquerque. Email:

(This article belongs to the Special Issue: Intelligent Medical Decision Support Systems: Methods and Applications)

Computer Modeling in Engineering & Sciences 2024, 140(1), 1077-1102. https://doi.org/10.32604/cmes.2024.047806

Received 18 November 2023; Accepted 05 January 2024; Issue published 16 April 2024

Abstract

Large-scale wireless sensor networks (WSNs) play a critical role in monitoring dangerous scenarios and responding to medical emergencies. However, the inherent instability and error-prone nature of wireless links present significant challenges, necessitating efficient data collection and reliable transmission services. This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs. The primary goal is to enhance the reliability of data collection and transmission services, ensuring a comprehensive and practical approach. Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability. Additionally, it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops. These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios. Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes. The evaluation spans varying sensor densities, wireless channel conditions, and packet transmission rates, showcasing the protocol’s superiority in ensuring reliable and efficient data transfer. Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scale WSNs. By prioritizing fairness, reliability, and efficiency, the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services, thereby offering a valuable contribution to the field of medical event-driven WSNs.

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Keywords

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