CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks

In this paper, we design and evaluate an energy efficient data retrieval architecture for continuous aggregate queries in wireless sensor networks. We show how the modification of precision in one sensor affects the sample-reporting frequency of other sensors, and how the precisions of a group of se...

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Main Authors: HU, Wen, MISRA, Archan, SHOREY, Rajiv
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Language:English
Published: Institutional Knowledge at Singapore Management University 2006
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Online Access:https://ink.library.smu.edu.sg/sis_research/686
https://ink.library.smu.edu.sg/context/sis_research/article/1685/viewcontent/hu_percom06.pdf
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spelling sg-smu-ink.sis_research-16852019-02-25T07:20:39Z CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks HU, Wen MISRA, Archan SHOREY, Rajiv In this paper, we design and evaluate an energy efficient data retrieval architecture for continuous aggregate queries in wireless sensor networks. We show how the modification of precision in one sensor affects the sample-reporting frequency of other sensors, and how the precisions of a group of sensors may be collectively modified to achieve the target quality of information (QoI) with higher energy-efficiency. The proposed collective adaptive precision setting (CAPS) architecture is then extended to exploit the observed temporal correlation among successive sensor samples for even greater energy efficiency. Detailed simulations with synthetic and real data traces demonstrate how the combination of weak consistency semantics and temporal correlation can dramatically lower the energy consumption in practical sensor environments 2006-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/686 info:doi/10.1109/PERCOM.2006.14 https://ink.library.smu.edu.sg/context/sis_research/article/1685/viewcontent/hu_percom06.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Software Engineering
spellingShingle Software Engineering
HU, Wen
MISRA, Archan
SHOREY, Rajiv
CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks
description In this paper, we design and evaluate an energy efficient data retrieval architecture for continuous aggregate queries in wireless sensor networks. We show how the modification of precision in one sensor affects the sample-reporting frequency of other sensors, and how the precisions of a group of sensors may be collectively modified to achieve the target quality of information (QoI) with higher energy-efficiency. The proposed collective adaptive precision setting (CAPS) architecture is then extended to exploit the observed temporal correlation among successive sensor samples for even greater energy efficiency. Detailed simulations with synthetic and real data traces demonstrate how the combination of weak consistency semantics and temporal correlation can dramatically lower the energy consumption in practical sensor environments
format text
author HU, Wen
MISRA, Archan
SHOREY, Rajiv
author_facet HU, Wen
MISRA, Archan
SHOREY, Rajiv
author_sort HU, Wen
title CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks
title_short CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks
title_full CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks
title_fullStr CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks
title_full_unstemmed CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks
title_sort caps: energy-efficient processing of continuous aggregate queries in sensor networks
publisher Institutional Knowledge at Singapore Management University
publishDate 2006
url https://ink.library.smu.edu.sg/sis_research/686
https://ink.library.smu.edu.sg/context/sis_research/article/1685/viewcontent/hu_percom06.pdf
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