Title

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

Document Type

Conference Proceeding

Source of Publication

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

Publication Date

12-1-2005

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.

ISBN

1595931546

Volume

3

First Page

1295

Last Page

1298

Disciplines

Computer Sciences

Keywords

Data stream management systems; Phenomenon detection; Sensor data rates; Tracking framework; Data processing; Electronic circuit tracking; Error detection; Query languages; Sensor data fusion; Sensors; Servers; Database systems

Scopus ID

33745607641

Indexed in Scopus

yes

Open Access

no

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