SRC: Sustainable Reactive Computing for Battery-free Edge Intelligence
Document Type
Conference Proceeding
Publication Date
1-1-2024
Abstract
This paper proposes SRC, a novel framework for efficient and reliable inference on battery-free smart Internet of Things (IoT) devices. SRC supports various configurations that follow reactive configuration while using the innovative state machine and a safe threshold mechanism to proactively halt operations, reducing store/load operations by up to 75%. It strategically stores essential convolutional neural network (CNN) data (layer, kernel, etc.) to optimize input/output feature map management. This reactive design allows seamless task resumption across power cycles, ensuring continuity in unpredictable energy environments. Experiments show significant gains, with SRC achieving on average ~ 81.85% reduction in read/write operations and approximately 57.18% improvement in sensing compared to conventional reactive methods based on the intermittent Energy Trace 1.
Identifier
85213312305 (Scopus)
ISBN
[9798331507862]
Publication Title
Proceedings - 15th International Green and Sustainable Computing Conference, IGSC 2024
External Full Text Location
https://doi.org/10.1109/IGSC64514.2024.00026
First Page
93
Last Page
98
Grant
2447566
Fund Ref
National Science Foundation
Recommended Citation
Tabrizchi, Sepehr; Taheri, Nedasadat; Feng, Justin; Sehatbakhsh, Nader; Pan, David Z.; and Roohi, Arman, "SRC: Sustainable Reactive Computing for Battery-free Edge Intelligence" (2024). Faculty Publications. 764.
https://digitalcommons.njit.edu/fac_pubs/764