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Implementation of Blockchain Consensus Algorithm on Embedded Architecture
Author(s) -
Tarek Frikha,
Faten Chaabane,
Nadhir Aouinti,
Omar Cheikhrouhou,
Nader Ben Amor,
Abdelfateh Kerrouche
Publication year - 2021
Publication title -
security and communication networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.446
H-Index - 43
eISSN - 1939-0114
pISSN - 1939-0122
DOI - 10.1155/2021/9918697
Subject(s) - blockchain , computer science , field programmable gate array , architecture , cloud computing , internet of things , key (lock) , embedded system , consensus algorithm , proof of work system , distributed computing , power consumption , certification , computer security , power (physics) , algorithm , operating system , art , physics , quantum mechanics , political science , law , visual arts
*e adoption of Internet of*ings (IoT) technology across many applications, such as autonomous systems, communication, and healthcare, is driving the market’s growth at a positive rate. *e emergence of advanced data analytics techniques such as blockchain for connected IoTdevices has the potential to reduce the cost and increase in cloud platform adoption. Blockchain is a key technology for real-time IoT applications providing trust in distributed robotic systems running on embedded hardware without the need for certification authorities. *ere are many challenges in blockchain IoT applications such as the power consumption and the execution time. *ese specific constraints have to be carefully considered besides other constraints such as number of nodes and data security. In this paper, a novel approach is discussed based on hybrid HW/SW architecture and designed for Proof of Work (PoW) consensus which is the most used consensus mechanism in blockchain. *e proposed architecture is validated using the Ethereum blockchain with the Keccak 256 and the field-programmable gate array (FPGA) ZedBoard development kit. *is implementation shows improvement in execution time of 338% and minimizing power consumption of 255% compared to the use of Nvidia Maxwell GPUs.

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