Energy efficiency comparison between data rate control and transmission power control algorithms for wireless body sensor networks | Zendy

Ali Hassan Sodhro | Zendy; Li Chen | Zendy; Aïcha Sekhari | Zendy; Yacine Ouzrout | Zendy; Wanqing Wu | Zendy

Open Access

Energy efficiency comparison between data rate control and transmission power control algorithms for wireless body sensor networks

Author(s) -

Ali Hassan Sodhro,

Li Chen,

Aïcha Sekhari,

Yacine Ouzrout,

Wanqing Wu

Publication year - 2018

Publication title -

international journal of distributed sensor networks

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.324

H-Index - 53

eISSN - 1550-1477

pISSN - 1550-1329

DOI - 10.1177/1550147717750030

Subject(s) - computer science , wireless sensor network , transmission (telecommunications) , power control , data transmission , energy consumption , real time computing , algorithm , wireless , power (physics) , energy (signal processing) , efficient energy use , computer network , telecommunications , electrical engineering , mathematics , statistics , engineering , physics , quantum mechanics

This article presents comparison between data rate or rate control, that is, video transmission rate control algorithm and transmission power control algorithms for two different cases. First, energy consumption due to high peak variable data rates in video transmission. Second, energy depletion due to high transmission power consumption and dynamic nature of wireless on-body channel. The former one focuses on constant (fixed) transmission power level and variable data rate (“severe” conditions), for example, medical monitoring of the emergency patients. The latter considers variable transmission power level and constant (fixed) data rate (“less severe” conditions), for example, electrocardiography measurement for patients in wireless body sensor networks. Besides, energy efficiency comparison analysis of battery-driven or video transmission rate control algorithm and transmission power control–driven or power control algorithm is presented. Finally, proposed algorithms are analyzed and categorized as energy-efficient and battery-friendly for medical applications in wireless body sensor networks.

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