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Research on the Link Quality Prediction Mechanism Based on ARIMA Model for Multi Person Cooperative Interaction

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Industrial IoT Technologies and Applications (Industrial IoT 2016)

Abstract

With the continuous enhancement of the hardware performance, the dynamic high speed sensing network in the small and medium size of the special industry is becoming more and more recognized and valued by the academic circles and enterprises, and in the process of multi - user interaction, the requirements on the quality of the link are also higher, but the high speed communication of the instability of the link quality and difficult to judge critical problem has not been solved. In this paper, we use the ARIMA model to predict the link quality of wireless multimedia sensor network, make the dynamic buffer and link switch in time. Finally through the experiment discovered after postprocessing forecast network to meet the real-time dynamic environment average closing package rate, stability and robustness are significantly improved.

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Acknowledgments

This article was supported by Fundamental Research Funds for the Central Universities (Grant numbers: SWU113066, XDJK2015C023), The ministry of education - Google co-operative professional comprehensive reform project-the base of Android application development technology (20710164), Special trade portable devices high-speed ad-hoc network protocol (41010815), and Southwest university school of computer and information science teaching team project.

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Correspondence to Heng Zhang .

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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Yao, S., Chen, C., Zhang, H. (2016). Research on the Link Quality Prediction Mechanism Based on ARIMA Model for Multi Person Cooperative Interaction. In: Wan, J., Humar, I., Zhang, D. (eds) Industrial IoT Technologies and Applications. Industrial IoT 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 173. Springer, Cham. https://doi.org/10.1007/978-3-319-44350-8_23

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  • DOI: https://doi.org/10.1007/978-3-319-44350-8_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44349-2

  • Online ISBN: 978-3-319-44350-8

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