Event composition and detection in data stream management systems
There has been a rising need to handle and process streaming kind of data. It is continuous, unpredictable, time-varying in nature and could arrive in multiple rapid streams. Sensor data, web clickstreams, etc. are the examples of streaming data. One of the important issues about streaming data m...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
Springer
2005
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/45362 |
| _version_ | 1848757261671858176 |
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| author | Mohania, M. Dhruv, S. Gupta, S. Bhowmick, S. Dillon, Tharam S. |
| author2 | Kim Viborg Andersen |
| author_facet | Kim Viborg Andersen Mohania, M. Dhruv, S. Gupta, S. Bhowmick, S. Dillon, Tharam S. |
| author_sort | Mohania, M. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | There has been a rising need to handle and process streaming kind of data. It is continuous, unpredictable, time-varying in nature and could arrive in multiple rapid streams. Sensor data, web clickstreams, etc. are the examples of streaming data. One of the important issues about streaming data management systems is that it needs to be processed in real-time. That is, active rules can be defined over data streams for making the system reactive. These rules are triggered based on the events detected on the data stream, or events detected while summarizing the data or combination of both. In this paper, we study the challenges involved in monitoring events in a Data Stream Management System (DSMS) and how they differ from the same in active databases. We propose an architecture for event composition and detection in a DSMS, and then discuss an algorithm for detecting composite events defined on both the summarized data streams and the streaming data. |
| first_indexed | 2025-11-14T09:25:17Z |
| format | Conference Paper |
| id | curtin-20.500.11937-45362 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:25:17Z |
| publishDate | 2005 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-453622022-10-20T06:34:47Z Event composition and detection in data stream management systems Mohania, M. Dhruv, S. Gupta, S. Bhowmick, S. Dillon, Tharam S. Kim Viborg Andersen John Debenham Roland Wagner Event Composition DSMS event detection data stream management systems There has been a rising need to handle and process streaming kind of data. It is continuous, unpredictable, time-varying in nature and could arrive in multiple rapid streams. Sensor data, web clickstreams, etc. are the examples of streaming data. One of the important issues about streaming data management systems is that it needs to be processed in real-time. That is, active rules can be defined over data streams for making the system reactive. These rules are triggered based on the events detected on the data stream, or events detected while summarizing the data or combination of both. In this paper, we study the challenges involved in monitoring events in a Data Stream Management System (DSMS) and how they differ from the same in active databases. We propose an architecture for event composition and detection in a DSMS, and then discuss an algorithm for detecting composite events defined on both the summarized data streams and the streaming data. 2005 Conference Paper http://hdl.handle.net/20.500.11937/45362 10.1007/11546924_74 Springer restricted |
| spellingShingle | Event Composition DSMS event detection data stream management systems Mohania, M. Dhruv, S. Gupta, S. Bhowmick, S. Dillon, Tharam S. Event composition and detection in data stream management systems |
| title | Event composition and detection in data stream management systems |
| title_full | Event composition and detection in data stream management systems |
| title_fullStr | Event composition and detection in data stream management systems |
| title_full_unstemmed | Event composition and detection in data stream management systems |
| title_short | Event composition and detection in data stream management systems |
| title_sort | event composition and detection in data stream management systems |
| topic | Event Composition DSMS event detection data stream management systems |
| url | http://hdl.handle.net/20.500.11937/45362 |