Scalable Performance Evaluation of Byzantine Fault-Tolerant Systems Using Network Simulation

Berger, Christian; Toumia, Sadok Ben; Reiser, Hans P.

doi:10.1109/prdc59308.2023.00030

2023 IEEE 28th Pacific Rim International Symposium on Dependable Computing (PRDC) 2023

DOI: 10.1109/prdc59308.2023.00030

|View full text |Cite

Scalable Performance Evaluation of Byzantine Fault-Tolerant Systems Using Network Simulation

Christian Berger,

Sadok Ben Toumia,

Hans P. Reiser

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Improved Fast-Response Consensus Algorithm Based on HotStuff

Wang,

Yuan,

Wang

et al. 2024

Sensors

View full text Add to dashboard Cite

Recent Byzantine Fault-Tolerant (BFT) State Machine Replication (SMR) protocols increasingly focus on scalability and security to meet the growing demand for Distributed Ledger Technology (DLT) applications across various domains. Current BFT consensus algorithms typically require a single leader node to receive and validate votes from the majority process and broadcast the results, a design challenging to scale in large systems. We propose a fast-response consensus algorithm based on improvements to HotStuff, aimed at enhancing transaction ordering speed and overall performance of distributed systems, even in the presence of faulty copies. The algorithm introduces an optimistic response assumption, employs a message aggregation tree to collect and validate votes, and uses a dynamically adjusted threshold mechanism to reduce communication delay and improve message delivery reliability. Additionally, a dynamic channel mechanism and an asynchronous leader multi-round mechanism are introduced to address multiple points of failure in the message aggregation tree structure, minimizing dependence on a single leader. This adaptation can be flexibly applied to real-world system conditions to improve performance and responsiveness. We conduct experimental evaluations to verify the algorithm’s effectiveness and superiority. Compared to the traditional HotStuff algorithm, the improved algorithm demonstrates higher efficiency and faster response times in handling faulty copies and transaction ordering.

show abstract

Improved Fast-Response Consensus Algorithm Based on HotStuff

Wang,

Yuan,

Wang

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Scalable Performance Evaluation of Byzantine Fault-Tolerant Systems Using Network Simulation

Cited by 1 publication

References 27 publications

Improved Fast-Response Consensus Algorithm Based on HotStuff

Improved Fast-Response Consensus Algorithm Based on HotStuff

Contact Info

Product

Resources

About