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Conceptual paper | Open Access

Using blockchain to build trusted LoRaWAN sharing server

Jun Lin1()Zhiqi Shen2Chunyan Miao3Siyuan Liu1
The Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly LILY, Nanyang Technological University, Singapore, Singapore
School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
The Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly LILY, Nanyang Technological University, Singapore, Singapore and School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
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Abstract

Purpose

With the rapid growth of the Internet of Things (IoT) market and requirement, low power wide area (LPWA) technologies have become popular. In various LPWA technologies, Narrow Band IoT (NB-IoT) and long range (LoRa) are two main leading competitive technologies. Compared with NB-IoT networks, which are mainly built and managed by mobile network operators, LoRa wide area networks (LoRaWAN) are mainly operated by private companies or organizations, which suggests two issues: trust of the private network operators and lack of network coverage. This study aims to propose a conceptual architecture design of a blockchain built-in solution for LoRaWAN network servers to solve these two issues for LoRaWAN IoT solution.

Design/methodology/approach

The study proposed modeling, model analysis and architecture design.

Findings

The proposed solution uses the blockchain technology to build an open, trusted, decentralized and tamper-proof system, which provides the indisputable mechanism to verify that the data of a transaction has existed at a specific time in the network.

Originality/value

To the best of our knowledge, this is the first work that integrates blockchain technology and LoRaWAN IoT technology.

References

 
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International Journal of Crowd Science
Pages 270-280
Cite this article:
Lin J, Shen Z, Miao C, et al. Using blockchain to build trusted LoRaWAN sharing server. International Journal of Crowd Science, 2017, 1(3): 270-280. https://doi.org/10.1108/IJCS-08-2017-0010
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