Phenomenon-aware stream query processing

M. H. Ali, Mohamed F. Mokbel, Walid G. Aref

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


Spatio-temporal data streams that are generated from mobile stream sources (e.g., mobile sensors) experience similar environmental conditions that result in distinct phenomena. Several research efforts are dedicated to detect and track various phenomena inside a data stream management system (DSMS). In this paper, we use the detected phenomena to reduce the demand on the DSMS resources. The main idea is to let the query processor observe the input data streams at the phenomena level. Then, each incoming continuous query is directed only to those phenomena that participate in the query answer. Two levels of indexing are employed, a phenomenon index and a query index. The phenomenon index provides a fine resolution view of the input streams that participate in a particular phenomenon. The query index utilizes the phenomenon index to maintain a query deployment map in which each input stream is aware of the set of continuous queries that the stream contributes to their answers. Both indices are updated dynamically in response to the evolving nature of phenomena and to the mobility of the stream sources. Experimental results show the efficiency of this approach with respect to the accuracy of the query result and the resource utilization of the DSMS.

Original languageEnglish (US)
Title of host publicationProceedings - 8th International Conference on Mobile Data Management, MDM 2007
Number of pages8
StatePublished - Dec 1 2007
Event8th International Conference on Mobile Data Management, MDM 2007 - Mannheim, Germany
Duration: May 7 2007May 11 2007

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
ISSN (Print)1551-6245


Other8th International Conference on Mobile Data Management, MDM 2007


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