Opportunistic Communication with Latency Guarantees for Intermittently-Powered Devices

Wardega, Kacper; Li, Wenchao; Kim, Hyoseung; Wu, Yawen; Jia, Zhenge; Hu, Jingtong

doi:10.23919/date54114.2022.9774732

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Fig. 3: System Framework energy buffers [29], energy-aware memory mapping [30], communication on IPDs [31], and zero-power timekeeping methods [32]. They contribute to expanding the application scope of IPDs and our work does not conflict with them.…”

Section: Energy Controllermentioning

confidence: 99%

Energy-Adaptive Real-time Sensing for Batteryless Devices

Karimi

Wang

Kim

2022

2022 IEEE 28th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)

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This paper presents CARTOS, a charging-aware real-time operating system designed to enhance the functionality of intermittently-powered batteryless devices (IPDs) for various Internet of Things (IoT) applications. While IPDs offer significant advantages such as extended lifespan and operability in extreme environments, they pose unique challenges, including the need to ensure forward progress of program execution amidst variable energy availability and maintaining reliable real-time time behavior during power disruptions. To address these challenges, CARTOS introduces a mixed-preemption scheduling model that classifies tasks into computational and peripheral tasks, and ensures their efficient and timely execution by adopting justin-time checkpointing for divisible computation tasks and uninterrupted execution for indivisible peripheral tasks. CARTOS also supports processing chains of tasks with precedence constraints and adapts its scheduling in response to environmental changes to offer continuous execution under diverse conditions. CARTOS is implemented with new APIs and components added to FreeRTOS but is designed for portability to other embedded RTOSs. Through real hardware experiments and simulations, CARTOS exhibits superior performance over state-of-the-art methods, demonstrating that it can serve as a practical platform for developing resilient, real-time sensing applications on IPDs.

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