Adaptive stream query processing approach for Linked Stream Data

Zia Ush Shamszaman

Adaptive stream query processing approach for Linked Stream Data

Department of Computing & Games

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Over the last few years several stream query processors havebeen proposed for efficient processing of Linked Stream Data (LSD).Multiple aspects can affect the performance and correctness of the re-sults produced by the query processors, including operational semanticsof linked streams, query execution method, and target domain. Howeverexisting approaches to stream query processing lack the adaptability toreact to changing requirements of the applications and properties of theunderlying data streams. The goal of this research is to design a moreflexible and adaptive stream query processing approach which enablesstream query processing approaches to adapt according to the require-ments of the applications and to the characteristics of the data streams.The adaptive approach will support efficient processing of larger amountof data by mitigating computational cost and network traffic and will beable to serve a broader category of real-time applications efficiently dueto its adaptive nature.

Original language	English
Title of host publication	Web Reasoning and Rule Systems - 8th International Conference, RR 2014, Proceedings
Editors	Roman Kontchakov, Marie-Laure Mugnier
Publisher	Springer-Verlag
Pages	251-252
Number of pages	2
ISBN (Print)	9783319111124
Publication status	Published - 2014
Event	8th International Conference on Web Reasoning and Rule Systems - Athens, Greece Duration: 15 Sept 2014 → 17 Sept 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8741 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Web Reasoning and Rule Systems
Abbreviated title	RR 2014
Country/Territory	Greece
City	Athens
Period	15/09/14 → 17/09/14

Bibliographical note

Funding Information:
★This research has been partially supported by Science Foundation Ireland (SFI) under grant No. SFI/12/RC/2289 and EU FP7 CityPulse Project under grant No.603095. http://www.ict-citypulse.eu.

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

Cite this

Shamszaman, Z. U. (2014). Adaptive stream query processing approach for Linked Stream Data. In R. Kontchakov, & M.-L. Mugnier (Eds.), Web Reasoning and Rule Systems - 8th International Conference, RR 2014, Proceedings (pp. 251-252). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8741 LNCS). Springer-Verlag.

Shamszaman, Zia Ush. / Adaptive stream query processing approach for Linked Stream Data. Web Reasoning and Rule Systems - 8th International Conference, RR 2014, Proceedings. editor / Roman Kontchakov ; Marie-Laure Mugnier. Springer-Verlag, 2014. pp. 251-252 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Over the last few years several stream query processors havebeen proposed for efficient processing of Linked Stream Data (LSD).Multiple aspects can affect the performance and correctness of the re-sults produced by the query processors, including operational semanticsof linked streams, query execution method, and target domain. Howeverexisting approaches to stream query processing lack the adaptability toreact to changing requirements of the applications and properties of theunderlying data streams. The goal of this research is to design a moreflexible and adaptive stream query processing approach which enablesstream query processing approaches to adapt according to the require-ments of the applications and to the characteristics of the data streams.The adaptive approach will support efficient processing of larger amountof data by mitigating computational cost and network traffic and will beable to serve a broader category of real-time applications efficiently dueto its adaptive nature.",

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note = "Funding Information: ★This research has been partially supported by Science Foundation Ireland (SFI) under grant No. SFI/12/RC/2289 and EU FP7 CityPulse Project under grant No.603095. http://www.ict-citypulse.eu. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 8th International Conference on Web Reasoning and Rule Systems, RR 2014 ; Conference date: 15-09-2014 Through 17-09-2014",

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Shamszaman, ZU 2014, Adaptive stream query processing approach for Linked Stream Data. in R Kontchakov & M-L Mugnier (eds), Web Reasoning and Rule Systems - 8th International Conference, RR 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8741 LNCS, Springer-Verlag, pp. 251-252, 8th International Conference on Web Reasoning and Rule Systems, Athens, Greece, 15/09/14.

Adaptive stream query processing approach for Linked Stream Data. / Shamszaman, Zia Ush.
Web Reasoning and Rule Systems - 8th International Conference, RR 2014, Proceedings. ed. / Roman Kontchakov; Marie-Laure Mugnier. Springer-Verlag, 2014. p. 251-252 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8741 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N1 - Funding Information: ★This research has been partially supported by Science Foundation Ireland (SFI) under grant No. SFI/12/RC/2289 and EU FP7 CityPulse Project under grant No.603095. http://www.ict-citypulse.eu. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.

PY - 2014

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AB - Over the last few years several stream query processors havebeen proposed for efficient processing of Linked Stream Data (LSD).Multiple aspects can affect the performance and correctness of the re-sults produced by the query processors, including operational semanticsof linked streams, query execution method, and target domain. Howeverexisting approaches to stream query processing lack the adaptability toreact to changing requirements of the applications and properties of theunderlying data streams. The goal of this research is to design a moreflexible and adaptive stream query processing approach which enablesstream query processing approaches to adapt according to the require-ments of the applications and to the characteristics of the data streams.The adaptive approach will support efficient processing of larger amountof data by mitigating computational cost and network traffic and will beable to serve a broader category of real-time applications efficiently dueto its adaptive nature.

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Shamszaman ZU. Adaptive stream query processing approach for Linked Stream Data. In Kontchakov R, Mugnier ML, editors, Web Reasoning and Rule Systems - 8th International Conference, RR 2014, Proceedings. Springer-Verlag. 2014. p. 251-252. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Adaptive stream query processing approach for Linked Stream Data

Abstract

Publication series

Conference

Bibliographical note

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