Materialized In-Network View for Spatial Aggregation Queries in Wireless Sensor Network

Wireless sensor networks composed of battery-powered sensor nodes are invaluable instruments for remote environment sensing. For sensor network applications, sensed readings are often collected in the form of aggregated data from a portion of a sensor network as requested by spatial aggregation quer...

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Main Authors: LEE, Ken C. K., ZHENG, Baihua, LEE, Wang-chien, Winter, Julian
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Language:English
Published: Institutional Knowledge at Singapore Management University 2007
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Online Access:https://ink.library.smu.edu.sg/sis_research/1240
http://dx.doi.org/10.1016/j.isprsjprs.2007.03.006
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spelling sg-smu-ink.sis_research-22392011-01-22T04:07:53Z Materialized In-Network View for Spatial Aggregation Queries in Wireless Sensor Network LEE, Ken C. K. ZHENG, Baihua LEE, Wang-chien Winter, Julian Wireless sensor networks composed of battery-powered sensor nodes are invaluable instruments for remote environment sensing. For sensor network applications, sensed readings are often collected in the form of aggregated data from a portion of a sensor network as requested by spatial aggregation queries. In a large distributed sensor network, queries can be issued from various locations at any time. Existing in-network query execution techniques execute queries independently that considerably overconsumes the precious energy of sensor nodes. As a result, the lifespan of a sensor network is inevitably shortened. In this paper, we propose a Materialized In-Network View (MINV) framework that precalculates aggregated data from clusters of sensor nodes as intermediate query results preserved in the network and made ready for queries. The executions of queries are performed as simple collections of these aggregated data. Thus, the quantities and sizes of messages transmitted among sensor nodes can be greatly reduced, thus prolonging the lifetime of a sensor network. Through extensive simulations, the effectiveness of our proposed framework is validated. 2007-10-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/1240 info:doi/10.1016/j.isprsjprs.2007.03.006 http://dx.doi.org/10.1016/j.isprsjprs.2007.03.006 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University simulation collections energy Environment instruments Aggregation aggregation networks Databases and Information Systems Numerical Analysis and Scientific Computing
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic simulation
collections
energy
Environment
instruments
Aggregation
aggregation
networks
Databases and Information Systems
Numerical Analysis and Scientific Computing
spellingShingle simulation
collections
energy
Environment
instruments
Aggregation
aggregation
networks
Databases and Information Systems
Numerical Analysis and Scientific Computing
LEE, Ken C. K.
ZHENG, Baihua
LEE, Wang-chien
Winter, Julian
Materialized In-Network View for Spatial Aggregation Queries in Wireless Sensor Network
description Wireless sensor networks composed of battery-powered sensor nodes are invaluable instruments for remote environment sensing. For sensor network applications, sensed readings are often collected in the form of aggregated data from a portion of a sensor network as requested by spatial aggregation queries. In a large distributed sensor network, queries can be issued from various locations at any time. Existing in-network query execution techniques execute queries independently that considerably overconsumes the precious energy of sensor nodes. As a result, the lifespan of a sensor network is inevitably shortened. In this paper, we propose a Materialized In-Network View (MINV) framework that precalculates aggregated data from clusters of sensor nodes as intermediate query results preserved in the network and made ready for queries. The executions of queries are performed as simple collections of these aggregated data. Thus, the quantities and sizes of messages transmitted among sensor nodes can be greatly reduced, thus prolonging the lifetime of a sensor network. Through extensive simulations, the effectiveness of our proposed framework is validated.
format text
author LEE, Ken C. K.
ZHENG, Baihua
LEE, Wang-chien
Winter, Julian
author_facet LEE, Ken C. K.
ZHENG, Baihua
LEE, Wang-chien
Winter, Julian
author_sort LEE, Ken C. K.
title Materialized In-Network View for Spatial Aggregation Queries in Wireless Sensor Network
title_short Materialized In-Network View for Spatial Aggregation Queries in Wireless Sensor Network
title_full Materialized In-Network View for Spatial Aggregation Queries in Wireless Sensor Network
title_fullStr Materialized In-Network View for Spatial Aggregation Queries in Wireless Sensor Network
title_full_unstemmed Materialized In-Network View for Spatial Aggregation Queries in Wireless Sensor Network
title_sort materialized in-network view for spatial aggregation queries in wireless sensor network
publisher Institutional Knowledge at Singapore Management University
publishDate 2007
url https://ink.library.smu.edu.sg/sis_research/1240
http://dx.doi.org/10.1016/j.isprsjprs.2007.03.006
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