The potential dangers of causal consistency and an explicit solution
2012 (English)In: Proceedings of the 3rd ACM Symposium on Cloud Computing, SoCC 2012, ACM , 2012Conference paper (Refereed)
Causal consistency is the strongest consistency model that is available in the presence of partitions and provides useful semantics for human-facing distributed services. Here, we expose its serious and inherent scalability limitations due to write propagation requirements and traditional dependency tracking mechanisms. As an alternative to classic potential causality, we advocate the use of explicit causality, or application-defined happens-before relations. Explicit causality, a subset of potential causality, tracks only relevant dependencies and reduces several of the potential dangers of causal consistency.
Place, publisher, year, edition, pages
ACM , 2012.
Causality, Convergence, Data dependencies, Explicit causality, Scalability, Semantic knowledge, Weak consistency
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-111813DOI: 10.1145/2391229.2391251ScopusID: 2-s2.0-84870505762ISBN: 978-145031761-0OAI: oai:DiVA.org:kth-111813DiVA: diva2:587498
3rd ACM Symposium on Cloud Computing, SoCC 2012, 14 October 2012 through 17 October 2012, San Jose, CA
QC 201301142013-01-142013-01-142014-01-24Bibliographically approved