Computer Vision Conference (CVC) 2026
21-22 May 2026
Publication Links
IJACSA
Special Issues
Computer Vision Conference (CVC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 10, 2025.
Abstract: The blockchain functions as a distributed database, where data is securely stored across multiple servers and network nodes. It exists in various forms, with Bitcoin, Ethereum, and Hyperledger being among the most prominent examples. To ensure the integrity and security of transactions within a blockchain network, a consensus algorithm is employed to establish agreement among participating nodes. Several types of consensus algorithms exist, each offering distinct features and operational mechanisms. One such algorithm is Authority Round (here defined as AuRa_ori), a member of the Proof-of-Authority (PoA) family supported by Parity clients. Previous studies have highlighted several vulnerabilities and performance limitations in AuRa_ori, particularly concerning transaction speed per second (TPS) and transaction throughput per second (TGS). This study specifically investigates the original AuRa algorithm alongside an improved version, termed AuRa_v1. In AuRa_v1, the transaction process is structured into four key phases: 1) leader assignment, 2) block proposal, 3) agreement, and 4) block commitment. However, inconsistencies and inefficiencies have been identified within certain phases of the original AuRa_ori, particularly during the leader assignment and agreement stages. In response, this study proposes an improved approach through AuRa_v1 to address these vulnerabilities. A detailed analysis is conducted to evaluate the impact of these vulnerabilities on TPS, TGS, and epoch time, followed by a performance comparison between AuRa_ori and AuRa_v1. Experimental results demonstrate that AuRa_v1 effectively resolves the identified performance issues, achieving a significant improvement. Specifically, AuRa_v1 records a 21.65% increase in both TPS and TGS compared to AuRa_ori, validating the effectiveness of the proposed enhancements.
Robiah Arifin, Wan Aezwani Wan Abu Bakar, Mustafa Man and Evizal Abdul Kadir. “Comparative Performance Analysis of Original AuRa and Improved AuRa Consensus Algorithms in Chain Hammer Digital Certificate Simulation”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.10 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0161025
@article{Arifin2025,
title = {Comparative Performance Analysis of Original AuRa and Improved AuRa Consensus Algorithms in Chain Hammer Digital Certificate Simulation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0161025},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0161025},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {10},
author = {Robiah Arifin and Wan Aezwani Wan Abu Bakar and Mustafa Man and Evizal Abdul Kadir}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.