Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Event Driven Architecture

  • K. Mani Chandy
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_570

Synonyms

Active Database, Active Database (Management) System; Event driven service-oriented architecture; Event processing systems; Sense and respond systems; Sensor network systems; Streaming database systems

Definitions

An event driven architecture is a software architecture for applications that detect and respond to events. An event is a significant change in the state of a system or its environment. The change may occur rapidly or slowly. The occurrence of an event in the past, or its current unfolding, or a prediction of an event in the future is deduced from data. An event-driven architecture includes sensors and other sources of data; processors that fuse data from multiple sensors and detect patterns over time, geographical locations, and other attributes and deduce events that occurred or predict events; responders for initiating actions in response to events; communication links for transferring information between components; and administrative software for monitoring,...

This is a preview of subscription content, log in to check access.

Recommended Reading

  1. 1.
    Babcock B, Babu S, Datar M, Motwani R, Widom J. Models and issues in data streams. In: Proceedings of the 21st ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems; 2002.Google Scholar
  2. 2.
    Chandy KM, Charpentier M, Capponi A. Towards a theory of events. In: Proceedings of the Inaugural International Conference on Distributed Event-based Systems; 2007. p. 180–7.Google Scholar
  3. 3.
    Deshpande A, Guestrin C, Madden SR, Hellerstein JM, Hong W. Model-driven data acquisition in sensor networks. In: Proceedings of the 30th International Conference on Very Large Data Bases; 2004.Google Scholar
  4. 4.
    Etzion O. Semantic approach to event processing. In: Proceedings of the Inaugural International Conference on Distributed Event-based Systems; 2007. p. 139.Google Scholar
  5. 5.
    Luckham D. The power of events: the power of complex event processing. Reading: Addison Wesley; 2002.Google Scholar
  6. 6.
    Muhl G, Fiege L, Pietzuch P. Distributed event based systems. Berlin: Springer; 2006.zbMATHGoogle Scholar
  7. 7.
    Schulte R. The business impact of event processing: why mainstream companies will soon use a lot more EDA. In: Proceedings of the IEEE Services Computing Workshop; 2006. p. 51.Google Scholar
  8. 8.
    Zhao F, Guibas L. Wireless sensor networks: an information processing approach. Los Altos: Morgan Kaufmann; 2004.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.California Institute of TechnologyPasadenaUSA

Section editors and affiliations

  • Opher Etzion
    • 1
  1. 1.IBM Software GroupIBM Haifa LabsHaifaIsrael