Abstract
Wireless sensor networks (WSNs) have provided many new opportunities for scientific studies and discoveries through continuously monitoring our world. However, one of the most critical challenges in environmental WSNs is their severe power limitation. While several approaches exist to overcome energy limitation, this paper focuses on systematically exploring temporal correlation in environmental observations through data compression approach for lossless, reliable and energy-efficient data gathering in WSNs for environmental monitoring. In light of this, we illustrate our developed approach and demonstrate its efficacy through an empirical study using real-world sensed data.
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