ABSTRACT
In this study, we propose SQUID, a software-based solution to predict the off-time of batteryless devices that operate in environments with short-term energy-harvesting stability. The key insight of SQUID is to sample the power in the environment when the device is on and use these samples to extrapolate the power availability when the device is off and charging its capacitor. Therefore, SQUID can predict the charging time of the batteryless sensors by using the predicted power availability. Our initial experiments showed that SQUID has a promising estimation accuracy by consuming up to 10 times less energy than existing timekeeping solutions.
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- Eren Çürük, Kasim Sinan Yıldırım, Przemyslaw Pawelczak, and Josiah Hester. 2019. On the Accuracy of Network Synchronization Using Persistent Hourglass Clocks. In Proceedings of the 7th International Workshop on Energy Harvesting & Energy-Neutral Sensing Systems. 35--41.Google Scholar
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- Kasım Sinan Yıldırım, Amjad Yousef Majid, Dimitris Patoukas, Koen Schaper, Przemyslaw Pawelczak, and Josiah Hester. 2018. Ink: Reactive kernel for tiny batteryless sensors. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems. 41--53.Google ScholarDigital Library
Index Terms
- Persistent Timekeeping Using Harvested Power Measurements
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