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arXiv · 2402.08739

SEASONS: Signal and Energy Aware Sensing on iNtermittent Systems

Pouya Mahdi Gholami·Henry Hoffmann
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Abstract

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.

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BibTeXRIS

Pouya Mahdi Gholami, Henry Hoffmann. 2024-02-13. SEASONS: Signal and Energy Aware Sensing on iNtermittent Systems. https://arxiv.org/abs/2402.08739

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