Abstract
Data replication is a common technique for programming distributed systems, and is often important to achieve performance or reliability goals. Unfortunately, the replication of data can compromise its consistency, and thereby break programs that are unaware. In particular, in weakly consistent systems, programmers must assume some responsibility to properly deal with queries that return stale data, and to avoid state corruption under conflicting updates. The fundamental tension between performance (favoring weak consistency) and correctness (favoring strong consistency) is a recurring theme when designing concurrent and distributed systems, and is both practically relevant and of theoretical interest.
In this course, we investigate how to understand and formalize consistency guarantees, and how we can determine if a system implementation is correct with respect to such specifications. We start by examining consensus, a classic problem in distributed systems, and then proceed to study various specifications and implementations of eventually consistent systems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
We talk more about failures later. For now, just assume that the set F of faulty processes is empty.
References
Brewer, E.A.: Towards robust distributed systems (abstract). In: PODC 2000 (2000)
Burckhardt, S.: Consistency in distributed systems. LASER Summer School Slide Decks (2013). http://sdrv.ms/1dWFsBQ
Burckhardt, S.: Principles of eventual consistency. Found. Trends Program. Lang. 1(1–2), 1–150 (2014)
Burrowsm, M.: The Chubby lock service for loosely-coupled distributed systems. In: Operating Systems Design and Implementation, pp. 335–350 (2006)
Cachin, C., Guerraoui, R., Rodrigues, L.: Introduction to Reliable and Secure Distributed Programming, 2nd edn. Springer, Heidelberg (2011)
Dill, D.L.: The murphi verification system. In: Computer Aided Verification, pp. 390–393 (1996)
Fischer, M.J., Lynch, N.A., Paterson, M.S.: Impossibility of distributed consensus with one faulty process. J. ACM 32, 374–382 (1982)
Gilbert, S., Lynch, N.: Brewer’s conjecture and the feasibility of consistent, available, partition-tolerant web services. SIGACT News 33(2), 51–59 (2002)
Hunt, P., Konar, M., Junqueira, F.P., Reed, B.: Zookeeper: wait-free coordination for internet-scale systems. In: Proceedings of the 2010 USENIX Conference on USENIX Annual Technical Conference, USENIXATC 2010, p. 11. USENIX Association, Berkeley (2010)
Lamport, L.: Time, clocks, and the ordering of events in a distributed system. Commun. ACM 21(7), 558–565 (1978)
Lamport, L.: The part-time parliament. ACM Trans. Comput. Syst. 16, 133–169 (1998)
Lloyd, W., Freedman, M.J., Kaminsky, M., Andersen, D.G.: Don’t settle foreventual: scalable causal consistency for wide-area storage with COPS. In: SOSP 2011 (2011)
Terry, D.: Replicated Data Consistency Explained Through Baseball (2011)
Thomas, R.H., Beranek, B.: A majority consensus approach to concurrency control for multiple copy databases. ACM Trans. Database Syst. 4, 180–209 (1979)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Burckhardt, S. (2015). Consistency in Distributed Systems. In: Meyer, B., Nordio, M. (eds) Software Engineering. LASER LASER 2013 2014. Lecture Notes in Computer Science(), vol 8987. Springer, Cham. https://doi.org/10.1007/978-3-319-28406-4_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-28406-4_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-28405-7
Online ISBN: 978-3-319-28406-4
eBook Packages: Computer ScienceComputer Science (R0)