Publicação
Threat-adaptive Byzantine Consensus
| Resumo: | Blockchain technology has sparked renewed interest in planetary-scale Byzantine fault-tolerant (BFT) state machine replication (SMR). While recent works have mainly focused on improving the scalability and throughput of these protocols, few have addressed latency. We present FLASHCONSENSUS, a novel transformation for optimizing the latency of quorum-based BFT consensus protocols. FLASHCONSENSUS uses an adaptive resilience threshold that enables faster transaction ordering when the system contains few faulty replicas. Our construction exploits adaptive weighted replication to automatically assign high voting power to the fastest replicas, forming small quorums that significantly speed up consensus. Even when using small quorums with a low resilience threshold, our protocol still satisfies the standard SMR safety and liveness guarantees, thanks to the careful integration of abortable SMR and BFT forensics techniques. To evaluate the efficacy of our approach, we conducted experiments with 21 replicas deployed on an emulated network resembling the AWS (Amazon Web Services) regions. The results show that FLASHCONSENSUS can order transactions with finality in under 0.4s, which is half the time a PBFT-like protocol takes in the same network and even less than this protocol running on the theoretically best possible internet links (transmitting at 67% of the speed of light). FLASHCONSENSUS represents a significant step forward in the quest for faster, more efficient BFT-based consensus protocols. Our approach has the potential to substantially improve the performance of BFT consensus protocols, which are critical to a wide range of distributed systems applications. By reducing latency, we can make BFT-based systems more responsive, improving the user experience and the overall effectiveness of these systems. |
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| Autores principais: | Rodrigues, Lívio Grifo Jorge |
| Assunto: | Replicação de Máquinas de Estado Tolerância a Faltas Bizantinas Auditoria em Sistemas Tolerantes a Faltas Bizantinas Consenso Teses de mestrado - 2023 |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| Resumo: | Blockchain technology has sparked renewed interest in planetary-scale Byzantine fault-tolerant (BFT) state machine replication (SMR). While recent works have mainly focused on improving the scalability and throughput of these protocols, few have addressed latency. We present FLASHCONSENSUS, a novel transformation for optimizing the latency of quorum-based BFT consensus protocols. FLASHCONSENSUS uses an adaptive resilience threshold that enables faster transaction ordering when the system contains few faulty replicas. Our construction exploits adaptive weighted replication to automatically assign high voting power to the fastest replicas, forming small quorums that significantly speed up consensus. Even when using small quorums with a low resilience threshold, our protocol still satisfies the standard SMR safety and liveness guarantees, thanks to the careful integration of abortable SMR and BFT forensics techniques. To evaluate the efficacy of our approach, we conducted experiments with 21 replicas deployed on an emulated network resembling the AWS (Amazon Web Services) regions. The results show that FLASHCONSENSUS can order transactions with finality in under 0.4s, which is half the time a PBFT-like protocol takes in the same network and even less than this protocol running on the theoretically best possible internet links (transmitting at 67% of the speed of light). FLASHCONSENSUS represents a significant step forward in the quest for faster, more efficient BFT-based consensus protocols. Our approach has the potential to substantially improve the performance of BFT consensus protocols, which are critical to a wide range of distributed systems applications. By reducing latency, we can make BFT-based systems more responsive, improving the user experience and the overall effectiveness of these systems. |
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