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Analysis and Scheduling of a Battery-Less Mixed-Criticality System with Energy Uncertainty

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Published:23 October 2016Publication History
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Abstract

We consider a battery-less real-time embedded system equipped with an energy harvester. It scavenges energy from an environmental resource according to some stochastic patterns. The success of jobs is threatened in the case of energy shortage, which might be due to lack of harvested energy, losses originated from the super-capacitor self-discharge, as well as power consumption of executed tasks. The periodic real-time tasks of the system follow a dual-criticality model. In addition, each task has a minimum required success ratio that needs to be satisfied in steady state. We analytically evaluate the behavior of such a system in terms of its energy-related success ratio for a given schedule. Based on these results, we propose a scheduling algorithm that satisfies both temporal and success-ratio constraints of the jobs, while respecting task criticalities and corresponding system modes. The accuracy of the analytical method as well as its dependence on the numerical computations and other model assumptions are extensively discussed through comparison with simulation results. Also, the efficacy of the proposed scheduling algorithm is studied through comparison to some existing non-mixed- and mixed-criticality scheduling algorithms.

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  1. Analysis and Scheduling of a Battery-Less Mixed-Criticality System with Energy Uncertainty

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        • Published in

          cover image ACM Transactions on Embedded Computing Systems
          ACM Transactions on Embedded Computing Systems  Volume 16, Issue 1
          Special Issue on VIPES, Special Issue on ICESS2015 and Regular Papers
          February 2017
          602 pages
          ISSN:1539-9087
          EISSN:1558-3465
          DOI:10.1145/3008024
          Issue’s Table of Contents

          Copyright © 2016 ACM

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          Publication History

          • Published: 23 October 2016
          • Revised: 1 June 2016
          • Accepted: 1 June 2016
          • Received: 1 December 2015
          Published in tecs Volume 16, Issue 1

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