Executing in-network queries using SNEE

Ixent Galpin; Robert Taylor; Alasdair J G Gray; Christian Y A Brenninkmeijer; Alvaro A A Fernandes; Norman W. Paton

doi:10.1007/978-3-642-24577-0_15

Executing in-network queries using SNEE

Ixent Galpin, Robert Taylor, Alasdair J G Gray, Christian Y A Brenninkmeijer, Alvaro A A Fernandes, Norman W. Paton

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

Abstract

The SNEE query optimizer enables users to characterize data requests against wireless sensor networks (WSNs), using a declarative query language called SNEEql (SNEE for Sensor NEtwork Engine, described in [GBG+11], and publicly available at http://code.google.com/p/snee ). Queries are compiled into imperative query execution plans, which are translated into executable nesC source code. In this paper, we illustrate the lifecycle of a SNEEql query Q for in-network execution. This lifecycle encompasses the steps of preparatory metadata collection, followed by the compilation of Q into a query execution plan QEP, the dissemination of binary images implementing QEP throughout the WSN, and the generation of query results. © 2011 Springer-Verlag.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\|Lect. Notes Comput. Sci.
Publisher	Springer Nature
Pages	136-139
Number of pages	3
Volume	7051
ISBN (Print)	9783642245763
DOIs	https://doi.org/10.1007/978-3-642-24577-0_15
Publication status	Published - 2011
Event	28th British National Conference on Databases, BNCOD 2011 - Manchester Duration: 1 Jul 2011 → …

Conference

Conference	28th British National Conference on Databases, BNCOD 2011
City	Manchester
Period	1/07/11 → …

Keywords

Distributed Query Processing
In-network Processing
Stream Query Languages
Wireless Sensor Networks

Access to Document

10.1007/978-3-642-24577-0_15

Cite this

Galpin, I., Taylor, R., Gray, A. J. G., Brenninkmeijer, C. Y. A., Fernandes, A. A. A., & Paton, N. W. (2011). Executing in-network queries using SNEE. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci. (Vol. 7051, pp. 136-139). Springer Nature. https://doi.org/10.1007/978-3-642-24577-0_15

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author = "Ixent Galpin and Robert Taylor and Gray, {Alasdair J G} and Brenninkmeijer, {Christian Y A} and Fernandes, {Alvaro A A} and Paton, {Norman W.}",

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booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.",

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Galpin, I, Taylor, R, Gray, AJG, Brenninkmeijer, CYA, Fernandes, AAA & Paton, NW 2011, Executing in-network queries using SNEE. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. vol. 7051, Springer Nature, pp. 136-139, 28th British National Conference on Databases, BNCOD 2011, Manchester, 1/07/11. https://doi.org/10.1007/978-3-642-24577-0_15

Executing in-network queries using SNEE. / Galpin, Ixent; Taylor, Robert; Gray, Alasdair J G et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. Vol. 7051 Springer Nature, 2011. p. 136-139.

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

TY - GEN

T1 - Executing in-network queries using SNEE

AU - Galpin, Ixent

AU - Taylor, Robert

AU - Gray, Alasdair J G

AU - Brenninkmeijer, Christian Y A

AU - Fernandes, Alvaro A A

AU - Paton, Norman W.

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Y1 - 2011

N2 - The SNEE query optimizer enables users to characterize data requests against wireless sensor networks (WSNs), using a declarative query language called SNEEql (SNEE for Sensor NEtwork Engine, described in [GBG+11], and publicly available at http://code.google.com/p/snee ). Queries are compiled into imperative query execution plans, which are translated into executable nesC source code. In this paper, we illustrate the lifecycle of a SNEEql query Q for in-network execution. This lifecycle encompasses the steps of preparatory metadata collection, followed by the compilation of Q into a query execution plan QEP, the dissemination of binary images implementing QEP throughout the WSN, and the generation of query results. © 2011 Springer-Verlag.

AB - The SNEE query optimizer enables users to characterize data requests against wireless sensor networks (WSNs), using a declarative query language called SNEEql (SNEE for Sensor NEtwork Engine, described in [GBG+11], and publicly available at http://code.google.com/p/snee ). Queries are compiled into imperative query execution plans, which are translated into executable nesC source code. In this paper, we illustrate the lifecycle of a SNEEql query Q for in-network execution. This lifecycle encompasses the steps of preparatory metadata collection, followed by the compilation of Q into a query execution plan QEP, the dissemination of binary images implementing QEP throughout the WSN, and the generation of query results. © 2011 Springer-Verlag.

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KW - In-network Processing

KW - Stream Query Languages

KW - Wireless Sensor Networks

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M3 - Conference contribution

SN - 9783642245763

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BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.

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ER -

Executing in-network queries using SNEE

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