Abstract
Distributed applications are characterized by the fact that the processes they are made up of execute on possibly geographically dispersed nodes. An important problem the underlying distributed system has to solve lies in maintaining the consistency of the state that is shared by such processes. Unfortunately, the non-instantaneity of message transmissions and failure occurrences make this fundamental task far from being trivial. Of course, this difficulty depends on the type of consistency required by the application. Distributed programming models based on shared variables have been advocated by many researchers. Basically, a consistency criterion states which value has to be returned when a process reads a variable of the shared state. We think that there are two basic axes that help characterize consistency criteria: ordering and timeliness. The ordering axis defines the possible orders in which operations can be executed while returning values for read operations that are permitted by the consistency criterion. The timeliness axis defines how soon a value written by one process must become visible to others. By exploring these two axes, one can not only define versatile consistency criteria that meet the needs of diverse applications, but consistency levels can also be adapted based on available system resources or changing needs of an application. We believe that the characterization of consistency criteria using the orthogonal axes of ordering and timeliness helps us understand important issues related to shared objects in distributed 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
Preview
Unable to display preview. Download preview PDF.
References
Ahamad M., Hutto P.W., Neiger G., Burns J.E. and Kohli P., Causal memory: Definitions, Implementations and Programming. Dist. Computing, 9:37–49, 1995.
Ahamad M., Raynal M. and Thiakime G.,AnAdaptive Architecture for Causally Consistent Distributed Services. Distributed Systems Engineering Journal, 6(2):63–70, 1999.
Baldoni R., Mostefaoui A. and Raynal M., Causal Delivery of Messages with Real-Time Data in Unreliable Networks. Real-Time Systems J., 10(3):245–262, 1996.
Garg V.K. and Raynal M., Normality: a Correctness Condition for Concurrent Objects. Parallel Processing Letters, 9(1):123–134, 1999.
Herlihy M.P. and Wing J.L., Linearizability: a Correctness Condition for Concurrent Objects. ACM TOPLAS, 12(3):463–492, 1990.
Krishnamurthy S., Sanders W.H. and Cukier M., An Adaptive Framework for Tunable Consistency and Timeliness Replication. Proc. IEEE Int. Conf. on Dependable Systems and Networks (DSN’02), Whashington DC, June 2002.
Krishnaswamy V., Ahamad M., Raynal M. and Bakken D., Shared State Consistency for Time-Sensitive Distributed Applications. Proc. 21th IEEE Int. Conf. on Dist Comp Systems (ICDCS’02), pp. 606–614, Phoenix (AZ), April 2001.
Lamport L.,HowtoMake a Multiprocessor Computer that Correctly Executes Multiprocess Programs. IEEE Transactions on Computers, C28(9):690–691, 1979.
Mittal N. and Garg V.K., Consistency Conditions for Multi-Object Distributed Operations. Proc. 18th IEEE Int. Conf. on Distributed Computing Systems (ICDCS’98), pp. 582–589, Amsterdam (Netherland), 1998. Springer Verlag LNCS #938, pp. 224–241, Dagsthul Castle (Germany), 1994.
Pereira J., Rodrigues L. and Oliveira R., Reducing the Cost of Group Communcation with Semantic View Synchrony. Proc. IEEE Conf. on Dependable Systems and Networks (DSN’02), pp. 293–302, 2002.
Raynal M., Sequential Consistency as lazy Linearizability. Proc. 14th ACM Int. Symp. on Parallel Algorithms and Architectures (SPAA’02),Winnipeg (CA), 2002.
Raynal M., Thiakime G. and Ahamad M., From Causal to Serializable Transactions. BA, 15th ACM Symposium on Principles of Dist. Comp., pp. 310, 1996.
Singla A., Ramachandran U. and Hodgins J., Temporal Notions of Synchronization and Consistency in Beehive. Proc. 9th ACM Symposium on Parallel Architectures and Algorithms (SPAA’97), pp. 211–220, Newport (RI), 1997.
Yu, H. and Vahdat, A., Design and Evaluation of a Conit-based Continuous Consistency Model for Replicated Services. ACM TOCS, 20(3):239–282, 2002.
Theel O. and Raynal M., Static and Dynamic Adaptation of Transactional Consistency. Proc. 30th Int. Conference on Systems Sciences (HICSS’97),Vol I:533–542, Maui (Hawaii), 1997.
Torres F., Ahamad M. and Raynal M., Lifetime-Based Consistency for Distributed Objects. Proc. 12th Int. Symposium on Distributed Computing (DISC’98), Springer Verlag #1499, Andros, Greece, pp. 378–392, 1998.
Torres F., Ahamad M. and Raynal M., Timed Consistency for Shared Distributed Objects. Proc. 18th ACM Int. Symposium on Principles of Distributed Computing (PODC’99), Atlanta, pp. 163–172, 1999.
Torres F., Ahamad M. and Raynal M., Real-Time Based Consistency Models for Distributed Objects. Journal of Computer Systems Science and Engineering, 17(2):133–142, 2002.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Ahamad, M., Raynal, M. (2003). Ordering vs Timeliness: Two Facets of Consistency?. In: Schiper, A., Shvartsman, A.A., Weatherspoon, H., Zhao, B.Y. (eds) Future Directions in Distributed Computing. Lecture Notes in Computer Science, vol 2584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-37795-6_14
Download citation
DOI: https://doi.org/10.1007/3-540-37795-6_14
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00912-2
Online ISBN: 978-3-540-37795-5
eBook Packages: Springer Book Archive