Fault-scalable Byzantine fault-tolerant services

By Michael Abd-El-Malek, G. R. Ganger, Garth R. Goodson, Michael K. Reiter, Jay J. Wylie. Symposium on Operating Systems Principles, 2005

466 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/ea8006995ae8fcf7f44fdcde398116da902a137a

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In Computer Networks and Communications

In Experimental and Cognitive Psychology

Citations in the corpus

A Survey of Distributed Consensus Protocols for Blockchain Networks (2019, background): “Well-known proposals include Quorum/Update (QU) [44], Hybrid Quorum (HQ) [45], Zyzzyva (using speculative execution) [46],”
RBFT: Redundant Byzantine Fault Tolerance (2013, background): “Byzantine Fault Tolerant (BFT) state machine replication is an efficient and effective approach to deal with arbitrary software and hardware faults [1], [5], [7], [8], [18].”
SBFT: A Scalable and Decentralized Trust Infrastructure (2018, methodology): “This approach was taken by QU [8] and HQ [32] and provides very good scalability when write contention is low.”
Making Byzantine Fault Tolerant Systems Tolerate Byzantine Faults (2009, unknown): “Note that this state-transfer procedure is self-tuning: if the system is unable to make progress because it cannot assemble quorums of PRE - PARE and COMMIT messages, then it will devote more time to processing catchup messages.”
ZooKeeper: Wait-free Coordination for Internet-scale Systems (2010, methodology): “There have been proposals of protocols for practical implementations of Byzantine-tolerant replicated state-machines [7, 10, 18, 1, 28].”
The Honey Badger of BFT Protocols (2016, background): “Many subsequent protocols offer improved performance, often through optimistic execution that provides excellent performance when there are no faults, clients do not contend much, and the network is well-behaved, and at least some progress otherwise [2,5,30,36,48].”
Mencius: Building Efficient Replicated State Machine for WANs (2008, unknown): “Q/U [1] proposes a scalable Byzantine fault-tolerant protocol.”
Narwhal and Tusk: a DAG-based mempool and efficient BFT consensus (2021, background): “The Narwhal Mempool is based on ideas from reliable broadcast [12] and reliable storage [2].”
Security and Privacy for Green IoT-Based Agriculture: Review, Blockchain Solutions, and Challenges (2020, methodology): “Note that there are more variations of PBFT algorithm such as Aardvark [128], Zyzzyva [129], HQ [130], Q/U [131], and Abstract [132].”
Algorand: Scaling Byzantine Agreements for Cryptocurrencies (2017, background): “Follow-on work has shown how to make Byzantine fault tolerance perform well and scale to dozens of servers [1, 17, 33].”
The Next 700 BFT Protocols (2015, background): “Quorum makes Aliph the first BFT protocol to achieve a latency of 2 one-way message delays while only requiring 3 f + 1 replicas (Q/U [Abd-El-Malek et al. 2005] has the same latency but requires 5 f + 1 replicas).”
Is the cure worse than the disease? overfitting in automated program repair (2015, background): “These evaluations have demonstrated that G&V techniques can repair a moderate number of bugs in medium-sized programs, as well as evaluated the monetary and time costs of automatic repair [32], the relationship between operator choices and test execution parameters and success [33,61], and human-rat”
Enhancing Bitcoin Security and Performance with Strong Consistency via Collective Signing (2016, background): “ByzCoin builds PBFT atop CoSi [54], a collective signing protocol that efﬁciently aggregates hundreds or thousands of signatures.”
Depot: Cloud Storage with Minimal Trust (2010, background): “For example, quorum and replicated state machine approaches [9, 24, 28, 29, 32, 41, 53, 54, 85, 95, 99, 100] tolerate failures by a fraction of servers.”
Attested append-only memory: making adversaries stick to their word (2007, result): “While the initial results along these lines were largely theoretical, in recent years there has been an increasing interest in producing practical Byzantine-fault tolerant systems, as exempliﬁed by PBFT [13], Q/U [6], Ivy [33], Plutus [20], SUNDR [26], HQ [14], and Zyzzyva [22].”
State Machine Replication for the Masses with BFT-SMART (2014, background): “, [3, 13, 16, 21–23, 31, 32], to cite just a few), but almost no practical use of these techniques in real deployments.”