Exploring Byzantine Generals Problem and Consensus Solutions
Speaker (s):
LIU Huiwen
PhD Candidate
School of Information Systems
Singapore Management University
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Date:
Time:
Venue:
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13 November 2020, Friday
10:00am - 11:00am
This is a virtual seminar. Please register by 11 November, the webex link will be sent to those who have registered on the following day.
We look forward to seeing you at this research seminar.
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About the Talk
Distributed ledger technology (DLT), initially fueled by the boom of Bitcoin, has started to attract increasing attention due to its great promise and potential for massive applications where a trusted third party is no longer needed. The Byzantine Generals Problem (BGP) is the analogy most often used to illustrate the requirement for consensus in distributed ledger technology (DLT). The Byzantine Generals Problem is a condition of distributed system, where components may fail and there is imperfect information on whether a component has failed, and the Byzantine fault-tolerant consensus protocols require agreement among a number of processes (or nodes) for a single data value in the presence of failed or unreliable processes. For this seminar, I will explore the Byzantine Generals Problem and the corresponding consensus solutions to lay the foundation for the subsequent consensus analysis and evaluation.
About the Speaker
Liu Huiwen received her master’s degree in the computer science and technology from Soochow University in 2017. She is currently working toward her Ph.D. degree at Singapore Management University (SMU). Her research interests mainly include distributed ledger technology (DLT), data asset and artificial intelligence, and she is working on the most important technical component in the DLT-based system (e.g., Bitcoin, Ethereum or EOS), namely consensus algorithms (e.g., PBFT, PoW or PoS), which serve to make sure a valid agreement is reached among a group of mutually distrusted nodes continuously in the DLT-based system, and try to apply the blockchain technology, especially the consensus algorithms to data asset governance.
