Affiliation:
1. University of California at Riverside, USA
Abstract
Distributed system replication is widely used as a means of fault-tolerance and scalability. However, it provides a spectrum of consistency choices that impose a dilemma for clients between correctness, responsiveness and availability. Given a sequential object and its integrity properties, we automatically synthesize a replicated object that guarantees state integrity and convergence and avoids unnecessary coordination. Our approach is based on a novel sufficient condition for integrity and convergence called well-coordination that requires certain orders between conflicting and dependent operations. We statically analyze the given sequential object to decide its conflicting and dependent methods and use this information to avoid coordination. We present novel coordination protocols that are parametric in terms of the analysis results and provide the well-coordination requirements. We implemented a tool called Hamsaz that can automatically analyze the given object, instantiate the protocols and synthesize replicated objects. We have applied Hamsaz to a suite of use-cases and synthesized replicated objects that are significantly more responsive than the strongly consistent baseline.
Funder
CRII: SHF: Certified Byzantine Fault-tolerant Systems
Publisher
Association for Computing Machinery (ACM)
Subject
Safety, Risk, Reliability and Quality,Software
Cited by
28 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Noctua: Towards Automated and Practical Fine-grained Consistency Analysis;Proceedings of the Nineteenth European Conference on Computer Systems;2024-04-22
2. LoRe: A Programming Model for Verifiably Safe Local-first Software;ACM Transactions on Programming Languages and Systems;2024-01-15
3. Anticipation of Method Execution in Mixed Consistency Systems;Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing;2023-03-27
4. Replicated Versioned Data Structures for Wide-Area Distributed Systems;IEEE Transactions on Parallel and Distributed Systems;2023-01-01
5. Comparing Causal Convergence Consistency Models;Networked Systems;2023