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Extending the lifetime of sensor networks using prediction and scheduling

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2 Author(s)
Jong Chern Lim ; UCD Sch. of Comput. & Inf., Univ. Coll. Dublin, Dublin ; Bleakley, C.J.

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.

Published in:

Intelligent Sensors, Sensor Networks and Information Processing, 2008. ISSNIP 2008. International Conference on

Date of Conference:

15-18 Dec. 2008