CRII: CSR: Opportunistic Computation Offloading for Battery-Free Computing Devices

The exponential growth of the Internet of Things (IoT) raises the question of how to power billions of new IoT devices sustainably without sacrificing their capabilities. Current battery-free IoT devices are powered by harvesting ambient energy, but with several shortcomings, including unpredictable energy availability, limited processing capability, and severely constrained memory resources. This project aims to address these challenges by leveraging the billions of persistently powered (i.e., battery- and wall-powered) IoT devices already in the field by offloading additional computation to them on demand. To realize this goal, this project will (1) study an integrated framework with heterogeneous radio support to perform partial computation on battery-free systems while also utilizing wall- or battery-powered edge devices for additional computation when needed; (2) design a scheduler that considers on-device computational uncertainty, harvestable energy characteristics, and timing constraints to determine optimal communication and computation strategies; and (3) investigate low overhead techniques to estimate the uncertainty of on-device computation via intermediate result analysis (e.g., from deep neural networks). The successful completion of this research could impact electronic waste (e-waste) by increasing the capabilities of battery-free computing devices. Enhanced battery-free computing capabilities could impact many fields, including healthcare (e.g., continuous health monitors), agriculture (e.g., soil moisture monitoring), space exploration (e.g., nanosatellites), and other scientific fields that require longitudinal, sustainable, zero-maintenance data gathering. The outcomes of this research will allow researchers and software developers across several scientific domains to utilize battery-free, sustainable computing for their applications and research. In addition to providing research opportunities to undergraduate and graduate students, the research outcomes will be integrated into university course curriculum. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.