Synonyms
Chronicle recognition; Event composition; Event control; Event trace analysis; Monitoring of real-time logic expressions
Definition
Event detection is the process of analyzing event streams in order to discover sets of events matching patterns of events in an event context. The event patterns and the event contexts define event types. If a set of events matching the pattern of an event type is discovered during the analysis, then subscribers of the event type should be signaled. The analysis typically entails filtering and aggregation of events.
Historical Background
Seminal work on event detection was done in HiPAC [1, 2] and Snoop [3, 4] as well as in ODE [5] and SAMOS [6]. Essentially, in Snoop, ODE, and SAMOS, different methods for realizing the matching of event detection were investigated. In Snoop, implementations of the event operators are structured according to the syntax tree of the event expression, where each node represents an event operator. The event operator...
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsRecommended Reading
Chakravarthy S, Blaustein B, Buchmann AP, Carey M, Dayal U, Goldhirsch D, Hsu M, Jauhuri R Ladin R, Livny M, McCarthy D, McKee R, Rosenthal A. HiPAC: a research project in active time-constrained database management. Technical report XAIT-89-02, Xerox advanced information technology; 1989.
Dayal U, Blaustein B, Buchmann A, Chakravarthy S, Hsu M, Ladin R, McCarty D, Rosenthal A, Sarin S, Carey MJ, Livny M, Jauharu R. The HiPAC project: combining active databases and timing constraints. ACM SIGMOD Rec. 1988;17(1):51–70.
Chakravarthy S, Krishnaprasad V, Anwar E, Kim SK Composite events for active database: semantics, contexts, and detection. In: Proceedings of the 20th International Conference on Very Large Data Bases; 1994. p. 606–17.
Chakravarthy S, Mishra D. Snoop: an event specification language for active databases. Knowl Data Eng. 1994;14(1):1–26.
Gehani NH, Jagadish HV, Schmueli O. COMPOSE – a system for composite event specification and detection. In: Advanced database concepts and research issues. Berlin: Springer; 1993.
Gatziu S. Events in an active object-oriented database system. PhD thesis, University of Zurich; 1994.
Mellin J. Resource-predictable and efficient monitoring of events. PhD thesis no 876, University of Linköping; 2004.
Dousson C, Gaborit P, Ghallab M. Situation recognition: representation and algorithms. In: Proceedings of the 13th International Joint Conference on AI; 1993. p. 166–72.
Chodrow SE, Jahanian F, Donner M. Run-time monitoring of real-time systems. In: Proceedings of the Real-Time Systems Symposium; 1991. p. 74–83.
Mansouri-Samani M, Sloman M. GEM: a generalized event monitoring language for distributed systems. IEE/IOP/BCS Distrib Syst Eng J. 1997;4(2):96–108.
Milne R, Nicol C, Ghallab M, Trave-massuyes L, Bousson K, Dousson C, Quevedo J, Martin JA, Guasch A. TIGER: real-time situation assessment of dynamic systems. Intell Syst Eng. 1994;3(3):103–24.
Bækgaard L, Godskesen JC. Real-time event control in active databases. J Syst Softw. 1997;42(3):263–71.
Motakis I, Zaniolo C. Composite temporal events in active database rules: a logic-oriented approach. In: Proceedings of the 4th International Conference on Deductive and Object-Oriented Databases; 1995. p. 19–37.
Bry F, Eckert M. Rule-based composite event queries: the language XChangeEQ and its semantics. In: Proceedings of the 1st International Conference on Web Reasoning and Rule Systems; 2007. p. 16–30.
Bry F, Eckert M. Temporal order optimizations of incremental joins for composite event detection. In: Proceedings of the Inaugural International Conference on Distributed Event-Based Systems; 2007. p. 85–90.
Geppert A, Berndtsson M, Lieuwen D, Roncancio C. Performance evaluation of object-oriented active database management systems using the BEAST benchmark. Theor Pract Object Syst. 1998;4(4):1–16.
Andler S, Hansson J, Eriksson J, Mellin J, Berndtsson M, Eftring B. DeeDS towards a distributed active and real-time database system. Special issue on real time data base systems. ACM SIGMOD Rec. 1996;25(1):38–51.
Berndtsson M, Mellin J, Högberg U. Visualization of the composite event detection process. In: Proceedings of the International Workshop on User Interfaces to Data Intensive Systems; 1999.
Liu G, Mok A, Yang E. Composite events for network event correlation. In: Proceedings of the IFIP/IEEE International Symposium on Integrated Network Management; 1999.
Carlsson J. Event pattern detection for embedded systems. PhD thesis no 44, Mälardalen University; 2007.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Mellin, J., Berndtsson, M. (2018). Event Detection. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_506
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_506
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering