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Enhancing Blockchain Consensus With FPGA: Accelerating Implementation for Efficiency

Jalel Ktari, Tarek Frikha, Monia Hamdi, Habib Hamam

2024IEEE Access15 citationsDOIOpen Access PDF

Abstract

Because of its versatility across various applications, Blockchain has emerged as a technology garnering significant interest. It has effectively addressed the challenge of transitioning from a low-trust, centralized ledger maintained by a single third-party to a high-trust, decentralized structure maintained by multiple entities, often referred to as validating nodes. Consequently, numerous blockchain systems have arisen for a multitude of purposes. Nevertheless, a considerable number of these blockchain systems are plagued by significant deficiencies concerning their performance and security. These issues have to be rectified before the realization of a widespread adoption. An essential element within any blockchain system is its foundational consensus algorithm, a crucial determinant of both its performance and security attributes. Consequently, to tackle the shortcomings observed in various blockchain systems, the hardware implementation of a series of established and innovative consensus algorithms was carried out as part of this work. This paper aims to compare and analyze the different consensus methods in blockchain, namely PoS (Proof of Stake), PoW (Proof of Work) and PoA (Proof of Authority) using VHDL (Very High-Speed Integrated Circuit Hardware Description Language). Each of these methods has unique characteristics that influence the validation of transactions and the addition of blocks to the blockchain. In this context, we aim to demonstrate the importance of optimizing consensus execution time via IPs (Intellectual Property) in VHDL. We also evaluate their impact on security, scalability and performance for IoT applications.

Topics & Concepts

BlockchainComputer scienceField-programmable gate arrayConsensus algorithmComputer securityEmbedded systemData scienceBlockchain Technology Applications and SecurityIoT and Edge/Fog ComputingAdvanced Memory and Neural Computing
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