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  5. Extending the Lifetime of Sensor Networks Using Prediction and Scheduling
 
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Extending the Lifetime of Sensor Networks Using Prediction and Scheduling

Author(s)
Lim, Jong Chern  
Bleakley, Chris J.  
Uri
http://hdl.handle.net/10197/7103
Date Issued
2008-12-18
Date Available
2015-09-25T09:06:48Z
Abstract
Power consumption in wireless sensor networks (WSNs) is a very important issue. Using measured sensor network data, this paper shows that it is possible to conserve a significant amount of energy through the proper use of data prediction and node scheduling without a significant loss in accuracy. Results show that it is possible to increase lifetime by up to 2600% at the cost of increasing average error by 0.5degC for temperature or 1.5% for humidity measurements. The four main design issues tackled are clustering, prediction, scheduling, and spike errors.
Sponsorship
Enterprise Ireland
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2008 IEEE
Subjects

Wireless sensor netwo...

Gaussian predictor

Scheduling

Entropy

DOI
10.1109/ISSNIP.2008.4762049
Language
English
Status of Item
Peer reviewed
Conference Details
International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), Syndey, Australia, 15 - 18 December, 2008
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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Extending_the_Lifetime_of_Sensor_Networks_Using_Prediction_and_Scheduling.pdf

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Format

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Checksum (MD5)

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Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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