TY - GEN
T1 - Eventual Consistency Formalized
AU - Sherratt, Edel
AU - Prinz, Andreas
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019/9/9
Y1 - 2019/9/9
N2 - Distribution of computation is well-known, and there are several frameworks, including some formal frameworks, that capture distributed computation. As yet, however, models of distributed computation are based on the idea that data is conceptually centralized. That is, they assume that data, even if it is distributed, is consistent. This assumption is not valid for many of the database systems in use today, where consistency is compromised to ensure availability and partition tolerance. Starting with an informal definition of eventual consistency, this paper explores several measures of inconsistency that quantify how far from consistency a system is. These measures capture key aspects of eventual consistency in terms of distributed abstract state machines. The definitions move from the traditional binary definition of consistency to more quantitative definitions, where the classical consistency is given by the highest possible level of consistency. Expressing eventual consistency in terms of abstract state machines allows models to be developed that capture distributed computation and highly available distributed data within a single framework
AB - Distribution of computation is well-known, and there are several frameworks, including some formal frameworks, that capture distributed computation. As yet, however, models of distributed computation are based on the idea that data is conceptually centralized. That is, they assume that data, even if it is distributed, is consistent. This assumption is not valid for many of the database systems in use today, where consistency is compromised to ensure availability and partition tolerance. Starting with an informal definition of eventual consistency, this paper explores several measures of inconsistency that quantify how far from consistency a system is. These measures capture key aspects of eventual consistency in terms of distributed abstract state machines. The definitions move from the traditional binary definition of consistency to more quantitative definitions, where the classical consistency is given by the highest possible level of consistency. Expressing eventual consistency in terms of abstract state machines allows models to be developed that capture distributed computation and highly available distributed data within a single framework
KW - Abstract state machine
KW - Distributed state
KW - Eventual consistency
KW - Formality
UR - http://www.scopus.com/inward/record.url?scp=85072872368&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-30690-8_15
DO - 10.1007/978-3-030-30690-8_15
M3 - Conference Proceeding (Non-Journal item)
SN - 978-3-030-30689-2
VL - 11753
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 249
EP - 265
BT - System Analysis and Modeling. Languages, Methods, and Tools for Industry 4.0 - 11th International Conference, SAM 2019, Proceedings
A2 - Fonseca i Casas, Pau
A2 - Sancho, Maria-Ribera
A2 - Sherratt, Edel
PB - Springer Nature
ER -