# Markovian model for Broadcast in Wireless Body Area Networks

**Authors:** Bruno Baynat (SU, LIP6, NPA), Gewu Bu (SU, LIP6, NPA), Maria, Potop-Butucaru (SU, LIP6, NPA, LINCS)

arXiv: 1906.05103 · 2019-06-13

## TL;DR

This paper introduces a novel Markovian analytical model for wireless body area networks (WBANs) to evaluate multi-hop broadcast protocols, validated against simulations, and used to analyze power-redundancy trade-offs.

## Contribution

It is the first to develop a Markovian model specifically for WBAN broadcast protocols, enabling analytical evaluation of performance and power-redundancy trade-offs.

## Key findings

- Model accurately predicts broadcast coverage and timing.
- Analytical evaluation of power-redundancy trade-offs.
- Validation confirms model's effectiveness against simulations.

## Abstract

Wireless body area networks became recently a vast field of investigation. A large amount of research in this field is dedicated to the evaluation of various communication protocols, e.g., broadcast or convergecast, against human body mobility. Most of the time this evaluation is done via simulations and in many situations only synthetic data is used for the human body mobility. In this paper we propose for the first time in Wireless Body Area Networks a Markovian analytical model specifically designed for WBAN networks. The main objective of the model is to evaluate the efficiency of a multi-hop transmission in the case of a diffusion-based broadcast protocol, with respect to various performance parameters (e.g., cover probability, average cover number, hitting probability or average cover time). We validate our model by comparing its results to simulation and show its accuracy. Finally, but not least, we show how our model can be used to analytically evaluate the trade-off between transmission power and redundancy, when the same message is broadcasted several times in order to increase the broadcast reliability while maintaining a low transmission power.

## Full text

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## Figures

13 figures with captions in the complete paper: https://tomesphere.com/paper/1906.05103/full.md

## References

17 references — full list in the complete paper: https://tomesphere.com/paper/1906.05103/full.md

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Source: https://tomesphere.com/paper/1906.05103