NILE-PDT: A phenomenon detection and tracking framework for data stream management systems

M. H. Ali, W. G. Aref, R. Bose, A. K. Elmagarmid, A. Helal, I. Kamel, M. F. Mokbel

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

28 Scopus citations

Abstract

In this demo, we present Nile-PDT, a Phenomenon Detection and Tracking framework using the Nile data stream management system. A phenomenon is characterized by a group of streams showing similar behavior over a period of time. The functionalities of Nile-PDT is split between the Nile server and the Nile-PDT application client. At the server side, Nile detects phenomenon candidate members and tracks their propagation incrementally through specific sensor network operators. Phenomenon candidate members are processed at the client side to detect phenomena of interest to a particular application. Nile-PDT is scalable in the number of sensors, the sensor data rates, and the number of phenomena. Guided by the detected phenomena, Nile-PDT tunes query processing towards sensors that heavily affect the monitoring of phenomenon propagation.

Original languageEnglish (US)
Title of host publicationVLDB 2005 - Proceedings of 31st International Conference on Very Large Data Bases
Pages1295-1298
Number of pages4
StatePublished - Dec 1 2005
EventVLDB 2005 - 31st International Conference on Very Large Data Bases - Trondheim, Norway
Duration: Aug 30 2005Sep 2 2005

Publication series

NameVLDB 2005 - Proceedings of 31st International Conference on Very Large Data Bases
Volume3

Other

OtherVLDB 2005 - 31st International Conference on Very Large Data Bases
CountryNorway
CityTrondheim
Period8/30/059/2/05

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