Abstract
Widely usage of LPWAN networks allows us to think about the further development of this technology, which develops networks to work not only with the star topology but also with a mesh topology. With such development, a procedure should be provided for determining the coordinates of nodes in the network. In this article, we propose a method for constructing a map of sensor nodes in the wireless mesh network. In particular, we analyzed rangefinder methods based on the received signal strength or the signal propagation duration to calculate the distances between nodes. With determined distances, a method is considered for constructing a three-dimensional model of each network fragment, then spatial transformations are carried out for the subsequent construction of a three-dimensional model of the whole network.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Queralta, J.P., Gia, T., Zou, Z., Tenhunen, H., Westerlund, T.: Comparative study of LPWAN technologies on unlicensed bands for m2m communication in the IoT: beyond LoRa and LoRaWAN. Proc. Comput. Sci. 155, 343–350 (2019). https://doi.org/10.1016/j.procs.2019.08.049
Kirichek, R., Vishnevsky, V., Pham, V.D., Koucheryavy, A.: Analytic model of a mesh topology based on LoRa technology. In: 2020 22nd International Conferenceon Advanced Communication Technology (ICACT), pp. 251–255. IEEE (2020). https://doi.org/10.23919/ICACT48636.2020.9061519
ITU. Recommendation ITU-R P.1411-9 Radio wave propagation data and prediction methods for planning outdoor short-range radio communication systems and local radio networks in the frequency range 300 MHz to 100 GHz. ITU (2017)
Semtech Corporation: datasheet SX1276/77/78/79 LoRa Transciever, p. 132 (2019)
ITU. Report ITU-R SM.2211-1 Comparison of methods for determining the geographical location of a signal source based on differences in arrival times and arrival angles. International Telecommunications Union, Geneva (2015)
Davison, M.L., Kamensky, V.S., Ayvazyan, S.A.: Multidimensional scaling: visual presentation methods. Finance and Statistics, Moscow (1988)
Lloyd, E., Lederman, W.: Handbook of Applied Statistics, vol. 2. Finance and Statistics, Moscow (1989)
Rogers, D., Adams, J.: Mathematical Foundations of Machine Graphics. World, Moscow (2001)
Kruskal, J.B.: Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29, 1–27 (1964). https://doi.org/10.1007/BF02289565
Acknowledgements
The publication has been prepared with the support of the grant from the President of the Russian Federation for state support of leading scientific schools of the Russian Federation according to the research project HIII-2604.2020.9.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Dai Pham, V., Grishin, I., Okuneva, D., Kirichek, R. (2020). Method of Constructing Node Map in Wireless Mesh Sensor Network. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2020 2020. Lecture Notes in Computer Science(), vol 12526. Springer, Cham. https://doi.org/10.1007/978-3-030-65729-1_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-65729-1_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-65728-4
Online ISBN: 978-3-030-65729-1
eBook Packages: Computer ScienceComputer Science (R0)