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Sensors 2017, 17(6), 1226; doi:10.3390/s17061226

Adaptive Data Aggregation and Compression to Improve Energy Utilization in Solar-Powered Wireless Sensor Networks

1
Department of Smart Systems Software, Soongsil University, Seoul 06978, Korea
2
Department of Software Convergence, Soongsil University, Seoul 06978, Korea
*
Author to whom correspondence should be addressed.
Academic Editors: Yuanyuan Yang and Songtao Guo
Received: 17 April 2017 / Revised: 17 May 2017 / Accepted: 24 May 2017 / Published: 27 May 2017
(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)
View Full-Text   |   Download PDF [578 KB, uploaded 27 May 2017]   |  

Abstract

A node in a solar-powered wireless sensor network (WSN) collects energy when the sun shines and stores it in a battery or capacitor for use when no solar power is available, in particular at night. In our scheme, each tiny node in a WSN periodically determines its energy budget, which takes into account its residual energy, and its likely acquisition and consumption. If it expects to acquire more energy than it can store, the data which has it has sensed is aggregated with data from other nodes, compressed, and transmitted. Otherwise, the node continues to sense data, but turns off its wireless communication to reduce energy consumption. We compared several schemes by simulation. Our scheme reduced the number of nodes forced to black out due to lack of energy so that more data arrives at the sink node. View Full-Text
Keywords: wireless sensor network; energy-harvesting; solar-powered; aggregation; compression wireless sensor network; energy-harvesting; solar-powered; aggregation; compression
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yoon, I.; Kim, H.; Noh, D.K. Adaptive Data Aggregation and Compression to Improve Energy Utilization in Solar-Powered Wireless Sensor Networks. Sensors 2017, 17, 1226.

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