A4 Article in conference proceedings
Compression methods for microclimate data based on linear approximation of sensor data (2019)


Väänänen, Olli; Hämäläinen, Timo (2019). Compression methods for microclimate data based on linear approximation of sensor data. In Galinina, Olga; Andreev, Sergey; Balandin, Sergey; Koucheryavy, Yevgeni (Eds.) NEW2AN 2019, ruSMART 2019 : Internet of Things, Smart Spaces, and Next Generation Networks and Systems : Proceedings of the 19th International Conference on Next Generation Wired/Wireless Networking, and 12th Conference on Internet of Things and Smart Spaces, Lecture Notes in Computer Science, 11660. Cham: Springer, 28-40. DOI: 10.1007/978-3-030-30859-9_3


JYU authors or editors


Publication details

All authors or editors: Väänänen, Olli; Hämäläinen, Timo

Parent publication: NEW2AN 2019, ruSMART 2019 : Internet of Things, Smart Spaces, and Next Generation Networks and Systems : Proceedings of the 19th International Conference on Next Generation Wired/Wireless Networking, and 12th Conference on Internet of Things and Smart Spaces

Parent publication editors: Galinina, Olga; Andreev, Sergey; Balandin, Sergey; Koucheryavy, Yevgeni

Place and date of conference: St.Petersburg, Russia, 26.-28.8.2019

ISBN: 978-3-030-30858-2

eISBN: 978-3-030-30859-9

Journal or series: Lecture Notes in Computer Science

ISSN: 0302-9743

eISSN: 1611-3349

Publication year: 2019

Number in series: 11660

Pages range: 28-40

Number of pages in the book: 759

Publisher: Springer

Place of Publication: Cham

Publication country: Switzerland

Publication language: English

DOI: http://doi.org/10.1007/978-3-030-30859-9_3

Open Access: Publication channel is not openly available

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/65554


Abstract

Edge computing is currently one of the main research topics in the field of Internet of Things. Edge computing requires lightweight and computationally simple algorithms for sensor data analytics. Sensing edge devices are often battery powered and have a wireless connection. In designing edge devices the energy efficiency needs to be taken into account. Pre-processing the data locally in the edge device reduces the amount of data and thus decreases the energy consumption of wireless data transmission. Sensor data compression algorithms presented in this paper are mainly based on data linearity. Microclimate data is near linear in short time window and thus simple linear approximation based compression algorithms can achieve rather good compression ratios with low computational complexity. Using these kind of simple compression algorithms can significantly improve the battery and thus the edge device lifetime. In this paper linear approximation based compression algorithms are tested to compress microclimate data.


Keywords: Internet of things; sensor networks; energy efficiency; algorithms

Free keywords: edge computing; internet of things; compression algorithm


Contributing organizations


Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1


Last updated on 2020-18-08 at 13:29