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Open Access

BGMM: A Body Gauss-Markov Based Mobility Model for Body Area Networks

Yi LiuDanpu Liu( )Guangxin Yue
School of Information and Communication Engineering, Beijing University of Post and Telecommunications, Beijing 100876, China.
School of Information Engineering, Beijing Institute of Fashion Technology, Beijing 100029, China
Jacob School, University of California, San Diego, CA 92122, USA.
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Abstract

Existing mobility models have limitations in their ability to simulate the movement of Wireless Body Area Network (WBAN) since body nodes do not exactly follow either classic mobility models or human contact distributions. In this paper, we propose a new mobility model called Body Gauss–Markov Mobility (BGMM) model, which is oriented specially to WBAN. First, we present the random Gauss-Markov mobility model as the most suitable theoretical basis for developing our new model, as its movement pattern can reveal real human body movements. Next, we examine the transfer of human movement states and derive a simplified mathematical Human Mobility Model (HMM). We then construct the BGMM model by combining the RGMM and HMM models. Finally, we simulate the traces of the new mobility model. We use four direct metrics in our proposed mobility model to evaluate its performance. The simulation results show that the proposed BGMM model performs with respect to the direct mobility metrics and can effectively represent a general WBAN-nodes movement pattern.

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Tsinghua Science and Technology
Pages 277-287
Cite this article:
Liu Y, Liu D, Yue G. BGMM: A Body Gauss-Markov Based Mobility Model for Body Area Networks. Tsinghua Science and Technology, 2018, 23(3): 277-287. https://doi.org/10.26599/TST.2018.9010005

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Received: 30 May 2017
Revised: 01 July 2017
Accepted: 21 July 2017
Published: 02 July 2018
© The author(s) 2018
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