In battery-powered embedded systems, the energy budget management is a critical aspect. For systems using unreliable power sources, e.g. solar panels, the continuous system operation is a challenging requirement. In such scenarios, effective management policies must rely on accurate energy estimations. In this paper we propose a measurement-based probabilistic approach to address the worst-case energy consumption (WCEC) estimation, coupled with a job admission algorithm for energy-constrained task scheduling. The overall goal is to demonstrate how the proposed approach can introduce benefits also in mission-critical systems, where unsafe energy budget estimations cannot be tolerated.

A Probabilistic Approach to Energy-Constrained Mixed-Criticality Systems

F. Reghenzani;G Massari;W. Fornaciari
2019

Abstract

In battery-powered embedded systems, the energy budget management is a critical aspect. For systems using unreliable power sources, e.g. solar panels, the continuous system operation is a challenging requirement. In such scenarios, effective management policies must rely on accurate energy estimations. In this paper we propose a measurement-based probabilistic approach to address the worst-case energy consumption (WCEC) estimation, coupled with a job admission algorithm for energy-constrained task scheduling. The overall goal is to demonstrate how the proposed approach can introduce benefits also in mission-critical systems, where unsafe energy budget estimations cannot be tolerated.
IEEE International Symposium on Low Power Electronics and Design
Embedded Systems, Energy Management, Probabilistic approaches
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1097615
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