SEASONS: Signal and Energy Aware Sensing on iNtermittent Systems
<|reference_start|>SEASONS: Signal and Energy Aware Sensing on iNtermittent Systems: Both energy-aware, batteryless intermittent systems and signal-aware adaptive sampling algorithms (ASA) aim to maximize sensor data accuracy under energy constraints in edge devices. Intuitively, combining both into a signal- & energy-aware solution would yield even better accuracy. Unfortunately, ASAs and intermittent systems rely on conflicting energy availability assumptions. So, a straightforward combination cannot achieve their combined benefits. Therefore, we propose SEASONS, the first framework for signal- and energy-aware intermittent systems. SEASONS buffers signal data in time, monitoring queue dynamics to ensure the data is reported within a user-specified latency constraint. SEASONS improves sensor data accuracy by 31% without increasing energy.<|reference_end|>
@article{gholami2024seasons:,
    title={SEASONS: Signal and Energy Aware Sensing on iNtermittent Systems},
    author={Pouya Mahdi Gholami, Henry Hoffmann},
    journal={arXiv preprint arXiv:2402.08739},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.08739},
    primaryClass={eess.SY cs.SY}
}