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Energy-efficient routing optimization algorithm in WBANs for patient monitoring

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Abstract

With the recent technological innovations for measuring the physiological characteristics in the human body, Wireless Body Area Networks (WBANs) have received much attention from the industry and academics. One of the feasible solutions provided by today’s WBAN is the continuous health monitoring in which sensors planted in various parts of the body, which measure and send information about physiological health status to a sink. The energy constraint WBAN has to perform these measurements with minimum energy consumptions of the nodes, maintaining the durable health monitoring process. This paper uses the meta-heuristic Genetic Algorithm (GA) to select the best routing path by calculating distances between the nodes under multiple scenarios, in contrast to the available direct distance optimization method. This study considers the use of energy by sensor nodes, number of rounds, number of sensors, the position of the deployed sensors and distance between the sensors. The comprehensive results show that direct distance optimization method drops more packets, i.e. 12,000 as compared to 8000 packets by the genetic algorithm when 8000 rounds were executed. The proposed optimization also outperforms the previous approach in terms of the number of dead nodes, which results in saving the energy to increase the lifetime of the WBAN significantly.

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Acknowledgements

The research work is financial supported by national high technology 863 program of china (No. 2015AA124103) and national key R&D program no 2016YFB05502001 and carried out in state key laboratory intelligent communication, navigation and micro-Nano system, Beijing university of posts and telecommunications, Beijing, China.

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Authors and Affiliations

  1. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China

    Muhammad Aamir Panhwar, Deng Zhong Liang & Kamran Ali Memon

  2. Mehran University of Engineering Technology, Jamshoro, Pakistan

    Muhammad Aamir Panhwar

  3. School of Computer Science and Technology, University of Science and Technology of China, Hefei, China

    Sijjad Ali Khuhro

  4. Prince Sultan University, Riyadh, Saudi Arabia

    Muhammad Aashed Khan Abbasi

  5. School of Information Communication Engineering, Beijing University of Posts and Telecommunication, Beijing, China

    Noor-ul-Ain

  6. Dawood University of Engineering and Technology, Karachi, Pakistan

    Zulfiqar Ali

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  1. Muhammad Aamir Panhwar
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  2. Deng Zhong Liang
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  3. Kamran Ali Memon
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  4. Sijjad Ali Khuhro
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  5. Muhammad Aashed Khan Abbasi
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  7. Zulfiqar Ali
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Correspondence to Muhammad Aamir Panhwar.

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Panhwar, M.A., Zhong Liang, D., Memon, K.A. et al. Energy-efficient routing optimization algorithm in WBANs for patient monitoring. J Ambient Intell Human Comput 12, 8069–8081 (2021). https://doi.org/10.1007/s12652-020-02541-7

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  • DOI: https://doi.org/10.1007/s12652-020-02541-7

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