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

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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NILE-PDT: a phenomenon detection and tracking framework for data stream management systems. / Ali, M.H.; Aref, W.G.; Bose, R. et al.
VLDB '05 Proceedings of the 31st international conference on Very large data bases. VLDB Endowment, 2005. p. 1295-1298.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Ali, MH, Aref, WG, Bose, R, Elmagarmid, AK, Helal, S, Kamel, I & Mokbel, MF 2005, NILE-PDT: a phenomenon detection and tracking framework for data stream management systems. in VLDB '05 Proceedings of the 31st international conference on Very large data bases. VLDB Endowment, pp. 1295-1298. <https://dl.acm.org/citation.cfm?id=1083755>

APA

Ali, M. H., Aref, W. G., Bose, R., Elmagarmid, A. K., Helal, S., Kamel, I., & Mokbel, M. F. (2005). NILE-PDT: a phenomenon detection and tracking framework for data stream management systems. In VLDB '05 Proceedings of the 31st international conference on Very large data bases (pp. 1295-1298). VLDB Endowment. https://dl.acm.org/citation.cfm?id=1083755

Vancouver

Ali MH, Aref WG, Bose R, Elmagarmid AK, Helal S, Kamel I et al. NILE-PDT: a phenomenon detection and tracking framework for data stream management systems. In VLDB '05 Proceedings of the 31st international conference on Very large data bases. VLDB Endowment. 2005. p. 1295-1298

Author

Ali, M.H. ; Aref, W.G. ; Bose, R. et al. / NILE-PDT : a phenomenon detection and tracking framework for data stream management systems. VLDB '05 Proceedings of the 31st international conference on Very large data bases. VLDB Endowment, 2005. pp. 1295-1298

Bibtex

@inproceedings{d714d839a44a4ed8970c74308fc69e0d,
title = "NILE-PDT: a phenomenon detection and tracking framework for data stream management systems",
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.",
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",
author = "M.H. Ali and W.G. Aref and R. Bose and A.K. Elmagarmid and Sumi Helal and I. Kamel and M.F. Mokbel",
year = "2005",
language = "English",
isbn = "1595931546",
pages = "1295--1298",
booktitle = "VLDB '05 Proceedings of the 31st international conference on Very large data bases",
publisher = "VLDB Endowment",

}

RIS

TY - GEN

T1 - NILE-PDT

T2 - a phenomenon detection and tracking framework for data stream management systems

AU - Ali, M.H.

AU - Aref, W.G.

AU - Bose, R.

AU - Elmagarmid, A.K.

AU - Helal, Sumi

AU - Kamel, I.

AU - Mokbel, M.F.

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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.

KW - Data stream management systems

KW - Phenomenon detection

KW - Sensor data rates

KW - Tracking framework

KW - Data processing

KW - Electronic circuit tracking

KW - Error detection

KW - Query languages

KW - Sensor data fusion

KW - Sensors

KW - Servers

KW - Database systems

M3 - Conference contribution/Paper

SN - 1595931546

SP - 1295

EP - 1298

BT - VLDB '05 Proceedings of the 31st international conference on Very large data bases

PB - VLDB Endowment

ER -