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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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 |
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Software Engineering HU, Wen MISRA, Archan SHOREY, Rajiv CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks |
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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 |
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HU, Wen MISRA, Archan SHOREY, Rajiv |
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HU, Wen MISRA, Archan SHOREY, Rajiv |
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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 |
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CAPS: Energy-Efficient Processing of Continuous Aggregate Queries in Sensor Networks |
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caps: energy-efficient processing of continuous aggregate queries in sensor networks |
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Institutional Knowledge at Singapore Management University |
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2006 |
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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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