Abstract
The paper describes two approaches to gathering measurement data about moving objects in wireless networks. The use of Fog computing technology makes it possible to relocate a part of calculations closer to measuring devices. The first approach suggests an estimation of telemetry quality into measuring points. The second approach uses prediction of telemetry quality by mining models. As a result, it became possible not only to redistribute the computational load, but also to significantly reduce the network traffic, which in turn brings the possibility to decrease the requirements for communication channels bandwidth and to use wireless networks for gathering telemetry.
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Acknowledgments
This work was supported by the Ministry of Education and Science of the Russian Federation in the framework of the state order “Organisation of Scientific Research”, task#2.6113.2017/6.7, and by grant of RFBR# 16-07-00625, supported by Russian President’s fellowship.
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Kholod, I., Plokhoi, N., Shorov, A. (2017). Fog Computing for Telemetry Gathering from Moving Objects. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. ruSMART NsCC NEW2AN 2017 2017 2017. Lecture Notes in Computer Science(), vol 10531. Springer, Cham. https://doi.org/10.1007/978-3-319-67380-6_46
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DOI: https://doi.org/10.1007/978-3-319-67380-6_46
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