Brewer's conjecture and the feasibility of consistent, available, partition-tolerant web services

By Seth Gilbert, Nancy A. Lynch. SIGA, 2002

2,075 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/bbe7a291e74d12d0bcad6f623d8a13e084b83255

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In Computer Networks and Communications

Citations in the corpus

PBFT vs Proof-of-Authority: Applying the CAP Theorem to Permissioned Blockchain (2018, methodology): “In this paper, we first derive the actual functioning of the two PoA algorithms, both from the scarse documentation and directly from the source code, then we conduct a qualitative analysis in terms of the CAP theorem [13] (that is, in a distributed system only two out of consistency, availability a”
On Patterns for Decentralized Control in Self-Adaptive Systems (2010, background): “However, ensuring that this data is consistent in a distributed system poses significant challenges in itself [15,19].”
A Survey of Large Scale Data Management Approaches in Cloud Environments (2011, background): “CAP theorem [45], [46] shows that a shared-data system can only choose at most two out of three properties: Consistency (all records are the same in all replicas), Availability (all replicas can accept updates or inserts), and tolerance to Partitions (the system still functions when distributed repl”
Solutions to Scalability of Blockchain: A Survey (2020, methodology): “Similar to the CAP theory [7] in the traditional field of the distributed system, the Blockchain Trilemma points out that three important properties of a”
Peer-to-peer support for massively multiplayer games (2004, background): “0 20 40 60 80 100 Percentage of nodes [0-10] [10-20] [20-30] [30-40] [40-50] [50-60] [60-70] [70-80] [80-90] [90-100] [100-110] [110-120] [120-130] [130-140] [140-150] [150-160] [160-170] [170-180] [180-190] [190-200] [200-210] [210-220]”
Data management in cloud environments: NoSQL and NewSQL data stores (2013, background): “satisfied by networked shared-data systems at the same time [21,22].”
Want to scale in centralized systems? Think P2P (2015, background): “…are very likely to execute increasingly on multiple data centers, at a global scale, while taking into account scalability, performance, and the inherent limitations of the FLP (Fischer, Lynch, Paterson) [29] and CAP (Consistency, Availability, and Partition Tolerance) [30] impossibility results.”
On scalability of software-defined networking (2013, neutral): “As stated in [7], it is not always feasible to achieve strong consistency while maintaining availability and partition tolerance.”
Depot: Cloud Storage with Minimal Trust (2010, methodology): “Such con.icts are unfortunate but unavoidable: they are provably the price of high availability [Gilbert and Lynch 2002].”
A comprehensive study of Convergent and Commutative Replicated Data Types (2011, background): “However, the associated serialisation bottleneck negatively impacts performance and scalability, while the CAP theorem [13] imposes a tradeoff between consistency and partition-tolerance.”
A Vademecum on Blockchain Technologies: When, Which, and How (2019, background): “An important impact on consensus has the “CAP” (Consistency, Availability, Partitioning) theorem [244], [245] stating that fault-tolerant distributed systems cannot guaran-”
Conflict-Free Replicated Data Types (2011, background): “The CAP theorem states that it is impossible to simultaneously ensure strong consistency (C), availability (A) and tolerate network partition (P) [8].”