Real Life Is Uncertain. Consensus Should Be Too!
Fuente:
arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866915794113265664 |
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| author | Frank, Reginald Ponnapalli, Soujanya Lomeli, Octavio Giridharan, Neil Aguilera, Marcos K Crooks, Natacha |
| author_facet | Frank, Reginald Ponnapalli, Soujanya Lomeli, Octavio Giridharan, Neil Aguilera, Marcos K Crooks, Natacha |
| contents | Modern distributed systems rely on consensus protocols to build a fault-tolerant-core upon which they can build applications. Consensus protocols are correct under a specific failure model, where up to $f$ machines can fail. We argue that this $f$-threshold failure model oversimplifies the real world and limits potential opportunities to optimize for cost or performance. We argue instead for a probabilistic failure model that captures the complex and nuanced nature of faults observed in practice. Probabilistic consensus protocols can explicitly leverage individual machine \textit{failure curves} and explore side-stepping traditional bottlenecks such as majority quorum intersection, enabling systems that are more reliable, efficient, cost-effective, and sustainable. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_11362 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Real Life Is Uncertain. Consensus Should Be Too! Frank, Reginald Ponnapalli, Soujanya Lomeli, Octavio Giridharan, Neil Aguilera, Marcos K Crooks, Natacha Distributed, Parallel, and Cluster Computing Databases Modern distributed systems rely on consensus protocols to build a fault-tolerant-core upon which they can build applications. Consensus protocols are correct under a specific failure model, where up to $f$ machines can fail. We argue that this $f$-threshold failure model oversimplifies the real world and limits potential opportunities to optimize for cost or performance. We argue instead for a probabilistic failure model that captures the complex and nuanced nature of faults observed in practice. Probabilistic consensus protocols can explicitly leverage individual machine \textit{failure curves} and explore side-stepping traditional bottlenecks such as majority quorum intersection, enabling systems that are more reliable, efficient, cost-effective, and sustainable. |
| title | Real Life Is Uncertain. Consensus Should Be Too! |
| topic | Distributed, Parallel, and Cluster Computing Databases |
| url | https://arxiv.org/abs/2602.11362 |