Continuous skyline monitoring over distributed data streams

Hua Lu; Yongluan Zhou; Jonas Haustad

doi:10.1007/978-3-642-13818-8_39

Continuous skyline monitoring over distributed data streams

Hua Lu, Yongluan Zhou, Jonas Haustad

7 Citations (Scopus)

Abstract

To monitor skylines over dynamic data, one needs to continuously update the skyline query results in order to reflect the new data values. This paper tackles the problem of continuous skyline monitoring on a central query server over dynamic data from multiple data sites. Simply sending the updates of tuple values to the server is cost-prohibitive. Therefore, we propose an approach where the central server collaborates with the data sites to monitor the possible skyline changes. By doing so, the processing load is distributed over all the nodes instead of only on the central server. Furthermore, the approach can minimize the bandwidth consumption between the server and the data sites, which is often critical in a widely distributed environment. Extensive experiments demonstrate that our proposal is efficient and effective.

Original language	English
Title of host publication	Scientific and Statistical Database Management : 22nd International Conference, SSDBM 2010, Heidelberg, Germany, June 30–July 2, 2010. Proceedings
Editors	Michael Gertz, Bertram Ludäscher
Number of pages	19
Publisher	Springer
Publication date	2010
Pages	565-583
ISBN (Print)	978-3-642-13817-1
ISBN (Electronic)	978-3-642-13818-8
DOIs	https://doi.org/10.1007/978-3-642-13818-8_39
Publication status	Published - 2010
Externally published	Yes
Event	22nd International Conference on Scientific and Statistical Database Management - Heidelberg, Germany Duration: 30 Jun 2010 → 2 Jul 2010 Conference number: 22

Conference

Conference	22nd International Conference on Scientific and Statistical Database Management
Number	22
Country/Territory	Germany
City	Heidelberg
Period	30/06/2010 → 02/07/2010

Series	Lecture notes in computer science
Volume	6187
ISSN	0302-9743

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10.1007/978-3-642-13818-8_39

Cite this

Lu, H., Zhou, Y., & Haustad, J. (2010). Continuous skyline monitoring over distributed data streams. In M. Gertz, & B. Ludäscher (Eds.), Scientific and Statistical Database Management: 22nd International Conference, SSDBM 2010, Heidelberg, Germany, June 30–July 2, 2010. Proceedings (pp. 565-583). Springer. Lecture notes in computer science Vol. 6187 https://doi.org/10.1007/978-3-642-13818-8_39

Continuous skyline monitoring over distributed data streams. / Lu, Hua; Zhou, Yongluan; Haustad, Jonas.

Scientific and Statistical Database Management: 22nd International Conference, SSDBM 2010, Heidelberg, Germany, June 30–July 2, 2010. Proceedings. ed. / Michael Gertz; Bertram Ludäscher. Springer, 2010. p. 565-583 (Lecture notes in computer science, Vol. 6187).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Lu, H, Zhou, Y & Haustad, J 2010, Continuous skyline monitoring over distributed data streams. in M Gertz & B Ludäscher (eds), Scientific and Statistical Database Management: 22nd International Conference, SSDBM 2010, Heidelberg, Germany, June 30–July 2, 2010. Proceedings. Springer, Lecture notes in computer science, vol. 6187, pp. 565-583, 22nd International Conference on Scientific and Statistical Database Management, Heidelberg, Germany, 30/06/2010. https://doi.org/10.1007/978-3-642-13818-8_39

Lu H, Zhou Y, Haustad J. Continuous skyline monitoring over distributed data streams. In Gertz M, Ludäscher B, editors, Scientific and Statistical Database Management: 22nd International Conference, SSDBM 2010, Heidelberg, Germany, June 30–July 2, 2010. Proceedings. Springer. 2010. p. 565-583. (Lecture notes in computer science, Vol. 6187). doi: 10.1007/978-3-642-13818-8_39

Lu, Hua ; Zhou, Yongluan ; Haustad, Jonas. / Continuous skyline monitoring over distributed data streams. Scientific and Statistical Database Management: 22nd International Conference, SSDBM 2010, Heidelberg, Germany, June 30–July 2, 2010. Proceedings. editor / Michael Gertz ; Bertram Ludäscher. Springer, 2010. pp. 565-583 (Lecture notes in computer science, Vol. 6187).

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abstract = "To monitor skylines over dynamic data, one needs to continuously update the skyline query results in order to reflect the new data values. This paper tackles the problem of continuous skyline monitoring on a central query server over dynamic data from multiple data sites. Simply sending the updates of tuple values to the server is cost-prohibitive. Therefore, we propose an approach where the central server collaborates with the data sites to monitor the possible skyline changes. By doing so, the processing load is distributed over all the nodes instead of only on the central server. Furthermore, the approach can minimize the bandwidth consumption between the server and the data sites, which is often critical in a widely distributed environment. Extensive experiments demonstrate that our proposal is efficient and effective.",

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Continuous skyline monitoring over distributed data streams

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