The Energy Harvesting Mode Abstraction
Abu Bakar, Josiah Hester
Abstract
Abu Bakar, Josiah Hester
Abstract
We propose a new abstraction for understanding energy harvesting behaviors in the wild, especially how these behaviors impact energy constrained and battery-free sensors. The Energy Harvesting Mode abstraction explores ways to make sense of energy harvesting behaviors. We take known energy harvesting datasets, and create a few of our own, then classify energy harvesting behavior into modes. Modes are periodic or repeated elements caused by systematic or fundamental attributes of the energy harvesting environment. We show the existence of these Energy Harvesting Modes using real world data and IV surfaces created with the Ekho emulator. We discuss the impacts and usage of this powerful abstraction, including enabling adaptation, test case generation, and efficiency analysis for energy harvesting and intermittently powered sensing devices.
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We propose a new abstraction for understanding energy harvesting behaviors in the wild, especially how these behaviors impact energy constrained and battery-free sensors. The Energy Harvesting Mode abstraction explores ways to make sense of energy harvesting behaviors. We take known energy harvesting datasets, and create a few of our own, then classify energy harvesting behavior into modes. Modes are periodic or repeated elements caused by systematic or fundamental attributes of the energy harvesting environment. We show the existence of these Energy Harvesting Modes using real world data and IV surfaces created with the Ekho emulator. We discuss the impacts and usage of this powerful abstraction, including enabling adaptation, test case generation, and efficiency analysis for energy harvesting and intermittently powered sensing devices.
Key concepts: Energy harvesting, Abstraction, Computer science, Energy (signal processing), Mode (computer interface), Adaptation (eye), Efficient energy use, Distributed computing