Distributed Data-Centric Adaptive Sampling for Cyber-Physical Systems

@article{Lee2015DistributedDA,
  title={Distributed Data-Centric Adaptive Sampling for Cyber-Physical Systems},
  author={Eun Kyung Lee and Hariharasudhan Viswanathan and Dario Pompili},
  journal={TAAS},
  year={2015},
  volume={9},
  pages={21:1-21:27}
}
A data-centric joint adaptive sampling and sleep scheduling solution, SILENCE, for autonomic sensor-based systems that monitor and reconstruct physical or environmental phenomena is proposed. Adaptive sampling and sleep scheduling can help realize the much needed resource efficiency by minimizing the communication and processing overhead in densely deployed autonomic sensor-based systems. The proposed solution exploits the spatiotemporal correlation in sensed data and eliminates redundancy in… CONTINUE READING

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Key Quantitative Results

  • Using our algorithms, we observed that we can achieve up to approximately 50% reduction in the number of nodes (REPs) transmitting data to the sink (remote processing center) while also signi.cantly saving on energy and communication costs (approximately 30%) in our experimental and simulation scenarios.

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