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Study of Data Transfer in a Heterogeneous LoRa-Satellite Network for the Internet of Remote Things.
Lysogor, Ivan; Voskov, Leonid; Rolich, Alexey; Efremov, Sergey.
Afiliación
  • Lysogor I; Laboratory of the Internet of Things and Cyber-physical Systems, National Research University Higher School of Economics, Moscow 101000, Russia.
  • Voskov L; Department of Computer Engineering, National Research University Higher School of Economics, Moscow 101000, Russia.
  • Rolich A; Department of Computer Engineering, National Research University Higher School of Economics, Moscow 101000, Russia. arolich@hse.ru.
  • Efremov S; School of Business Informatics, National Research University Higher School of Economics, Moscow 101000, Russia.
Sensors (Basel) ; 19(15)2019 Aug 01.
Article en En | MEDLINE | ID: mdl-31374980
ABSTRACT
In the absence of traditional communication infrastructures, the choice of available technologies for building data collection and control systems in remote areas is very limited. This paper reviews and analyzes protocols and technologies for transferring Internet of Things (IoT) data and presents an architecture for a hybrid IoT-satellite network, which includes a long range (LoRa) low power wide area network (LPWAN) terrestrial network for data collection and an Iridium satellite system for backhaul connectivity. Simulation modelling, together with a specialized experimental stand, allowed us to study the applicability of different methods of information presentation for the case of transmitting IoT data over low-speed satellite communication channels. We proposed a data encoding and packaging scheme called GDEP (Gateway Data Encoding and Packaging). It is based on the combination of data format conversion at the connection points of a heterogeneous network and message packaging. GDEP enabled the reduction of the number of utilized Short Burst Data (SBD) containers and the overall transmitted data size by almost five times.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2019 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2019 Tipo del documento: Article