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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2504.18649 |
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| _version_ | 1866909596549906432 |
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| author | Tonkikh, Andrei Arun, Balaji Xiang, Zhuolun Li, Zekun Spiegelman, Alexander |
| author_facet | Tonkikh, Andrei Arun, Balaji Xiang, Zhuolun Li, Zekun Spiegelman, Alexander |
| contents | In this paper, we present Raptr--a Byzantine fault-tolerant state machine replication (BFT SMR) protocol that combines strong robustness with high throughput, while attaining near-optimal theoretical latency. Raptr delivers exceptionally low latency and high throughput under favorable conditions, and it degrades gracefully in the presence of Byzantine faults and network attacks.
Existing high-throughput BFT SMR protocols typically take either pessimistic or optimistic approaches to data dissemination: the former suffers from suboptimal latency in favorable conditions, while the latter deteriorates sharply under minimal attacks or network instability. Raptr bridges this gap, combining the strengths of both approaches through a novel Prefix Consensus mechanism.
We implement Raptr and evaluate it against several state-of-the-art protocols in a geo-distributed environment with 100 replicas. Raptr achieves 260,000 transactions per second (TPS) with sub-second latency under favorable conditions, sustaining 610ms at 10,000 TPS and 755ms at 250,000 TPS. It remains robust under network glitches, showing minimal performance degradation even with a 1% message drop rate. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_18649 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Raptr: Prefix Consensus for Robust High-Performance BFT Tonkikh, Andrei Arun, Balaji Xiang, Zhuolun Li, Zekun Spiegelman, Alexander Distributed, Parallel, and Cluster Computing In this paper, we present Raptr--a Byzantine fault-tolerant state machine replication (BFT SMR) protocol that combines strong robustness with high throughput, while attaining near-optimal theoretical latency. Raptr delivers exceptionally low latency and high throughput under favorable conditions, and it degrades gracefully in the presence of Byzantine faults and network attacks. Existing high-throughput BFT SMR protocols typically take either pessimistic or optimistic approaches to data dissemination: the former suffers from suboptimal latency in favorable conditions, while the latter deteriorates sharply under minimal attacks or network instability. Raptr bridges this gap, combining the strengths of both approaches through a novel Prefix Consensus mechanism. We implement Raptr and evaluate it against several state-of-the-art protocols in a geo-distributed environment with 100 replicas. Raptr achieves 260,000 transactions per second (TPS) with sub-second latency under favorable conditions, sustaining 610ms at 10,000 TPS and 755ms at 250,000 TPS. It remains robust under network glitches, showing minimal performance degradation even with a 1% message drop rate. |
| title | Raptr: Prefix Consensus for Robust High-Performance BFT |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2504.18649 |