Extending the Lifetime of Sensor Networks Using Prediction and Scheduling
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|Title:||Extending the Lifetime of Sensor Networks Using Prediction and Scheduling||Authors:||Lim, Jong Chern
Bleakley, Chris J.
|Permanent link:||http://hdl.handle.net/10197/7103||Date:||18-Dec-2008||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.||Funding Details:||Enterprise Ireland||Type of material:||Conference Publication||Publisher:||IEEE||Copyright (published version):||2008 IEEE||Keywords:||Wireless sensor networks;Gaussian predictor;Scheduling;Entropy||DOI:||10.1109/ISSNIP.2008.4762049||Language:||en||Status of Item:||Peer reviewed||Conference Details:||International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), Syndey, Australia, 15 - 18 December, 2008|
|Appears in Collections:||Computer Science Research Collection|
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