RISC32‐E: Field programmable gate array based sensor node with queue system to support fast encryption in Industrial Internet of Things applications

Summary Industrial Internet of Things (IIoT) is an emerging technology that relies on the use of massively connected sensor nodes to gather industrial‐related data. The collected data are used for postanalysis to generate insights for reducing production down time, cost optimization, and predictive...

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Veröffentlicht in:International journal of circuit theory and applications 2020-08, Vol.48 (8), p.1209-1226
Hauptverfasser: See, Jin‐Chuan, Mok, Kai‐Ming, Lee, Wai‐Kong, Goh, Hock‐Guan
Format: Artikel
Sprache:eng
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Zusammenfassung:Summary Industrial Internet of Things (IIoT) is an emerging technology that relies on the use of massively connected sensor nodes to gather industrial‐related data. The collected data are used for postanalysis to generate insights for reducing production down time, cost optimization, and predictive maintenance. One of the key requirements for sensor node in such application is the data confidentiality; as such sensor data may potentially leak the manufacturing and industrial secret to their competitors. In this paper, a field programmable gate array (FPGA)‐based sensor node with Advanced Encryption Standard (AES) crypto‐processor is proposed to safeguard the sensor data. A novel queue system is proposed to further reduce the data processing time and energy consumption. The proposed queue system is able to achieve 1.48× speed up and ∼16% energy reduction, which makes it a competitive candidate for Industrial IoT applications. The technique developed in this paper can also be extended to implement FPGA‐based gateway with encryption feature, which is very useful for edge computing in IoT applications. This paper proposed a hardware queue system to support fast encryption. The fast encryption is beneficial for sensor nodes used in IIoT applications, where energy constraint is present. Experimental result indicates that, with the queue system, a 1.48× speed up and ~16% of energy reduction were achieved for the overall program execution.
ISSN:0098-9886
1097-007X
DOI:10.1002/cta.2797