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University of Greenwich

Improved blockchain - Proof-of-work consensus protocol - performance using machine learning

Abstract

dc:description.abstract

Blockchain technology has proven to be a secured and reliable technology by bringing security, trust and data integrity to a distributed system. It is a new paradigm that helps in the existence of cryptocurrency and eliminates the third party in a financial transaction. It has the potential to optimise, enhance and streamline many processes outside the cryptocurrency and financial sector but the adoption of the technology is limited by the hindering performance issue. Unfortunately, the current blockchain suffers a performance degrade with the increasing size because of the complexity of its consensus protocol known as Proof-of-Work (PoW). Many industries, researchers and organisation have been working on providing a solution to the performance issues of the technology but most of the proposed solutions has so far ended in proposing a newly designed protocol which ends up facing another issue referred to as the scalability issue; having to trade off one of security or decentralisation to get speed. To address the performance issue, the research has carried out experiments to clear pathways in identifying the specific problem and the outcome has identified the mining process, block size and scalability as the main factors affecting the performance of the technology. The research further investigated these factors and identified the time taken to generate a block as the most time-consuming task within the consensus process, regardless of the traffic, size or number of connected nodes. The research has also explored alternative ways of speeding the nonce finding process and identified machine learning as the best technique because of its ability to learn and predict. Using the quantitative approach of the research, different machine learning models were analysed and compared, and linear regression was identified as the best fit model for the research problem. The research used linear regression model Machine Learning technology to reduce the block generation time without sacrificing security or decentralisation of the proof-of-work consensus protocol. The model has achieved a 58 percent accuracy improvement on the traditional mining process. The model reduces the block generation time when tested on the blockchain simulation by an average of 4 seconds on the Ethereum network and a more significant reduction for the Bitcoin network depending on the computer hardware. In this thesis, blockchain is referred to as the blockchain that uses the PoW consensus protocol.

Degree

thesis:*
Name dc:type.qualificationname
phd
Level dc:type.qualificationlevel
doctoral
Grantor dc:publisher.institution
University of Greenwich
Year dc:date.issued
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ahmed, Mujistapha Safana
Advisors dc:contributor.advisor
  • Arafa, Yasmine
  • Ma, Jixin

Subjects

dc:subject × 1

Rights

Language dc:language
en

Chain of custody

source
Harvested from
University of Greenwich
Base URL
gala.gre.ac.uk/cgi/oai2
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Ahmed, Mujistapha Safana. Improved blockchain - Proof-of-work consensus protocol - performance using machine learning. doctoral thesis, University of Greenwich, 2021.