Emergency traffic adaptive MAC protocol for wireless body area networks based on prioritization

Autoři: Farhan Masud aff001;  Abdul Hanan Abdullah aff001;  Gaddafi Abdul-Salaam aff003
Působiště autorů: School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Johor, Malaysia aff001;  Department of Statistics & Computer Science, Faculty of Life Sciences Business Management, University of Veterinary and Animal Sciences, Lahore, Pakistan aff002;  Department of Computer Science, Kwame Nkrumah University of Science & Technology, Kumasi, Ashanti Region, Ghana aff003
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0225518


This paper proposes an emergency Traffic Adaptive MAC (eTA-MAC) protocol for WBANs based on Prioritization. The main advantage of the protocol is to provide traffic ranking through a Traffic Class Prioritization-based slotted-Carrier Sense Multiple Access/Collision Avoidance (TCP-CSMA/CA) scheme. The emergency traffic is handled through Emergency Traffic Class Provisioning-based slotted-CSMA/CA (ETCP-CSMA/CA) scheme. The emergency-based traffic adaptivity is provided through Emergency-based Traffic Adaptive slotted-CSMA/CA (ETA-CSMA/CA) scheme. The TCP-CSMA/CA scheme assigns a distinct, minimized and prioritized backoff period range to each traffic class in every backoff during channel access in Contention Access Period (CAP). The ETCP-CSMA/CA scheme delivers the sporadic emergency traffic that occurs at a single or multiple BMSN(s) instantaneously, with minimum delay and packet loss. It does this while being aware of normal traffic in the CAP. Then, the ETA-CSMA/CA scheme creates a balance between throughput and energy in the sporadic emergency situation with energy preservation of normal traffic BMSNs. The proposed protocol is evaluated using NS-2 simulator. The results indicate that the proposed protocol is better than the existing Medium Access Control (MAC) protocols by 86% decrease in packet delivery delay, 61% increase in throughput, and a 76% decrease in energy consumption.

Klíčová slova:

Algorithms – Blood pressure – Data management – Electrocardiography – Electroencephalography – Electromyography – Heart rate – Respiration


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2019 Číslo 12
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