Scheduling Mixed-Criticality (MC) workload is a challenging problem in real-time computing. Earliest Deadline First Virtual Deadline (EDF-VD) is one of the most famous scheduling algorithm with optimal speedup bound properties. However, when EDF-VD is used to schedule task sets using a model with additional or relaxed constraints, its scheduling properties change. Inspired by an application of MC to the scheduling of fault tolerant tasks, in this article, we propose two models for multiple criticality levels: the first is a specialization of the MC model, and the second is a generalization of it. We then show, via formal proofs and numerical simulations, that the former considerably improves the speedup bound of EDF-VD. Finally, we provide the proofs related to the optimality of the two models, identifying the need of new scheduling algorithms.

Mixed-Criticality with Integer Multiple WCETs and Dropping Relations: New Scheduling Challenges

F. Reghenzani;W. Fornaciari
2023-01-01

Abstract

Scheduling Mixed-Criticality (MC) workload is a challenging problem in real-time computing. Earliest Deadline First Virtual Deadline (EDF-VD) is one of the most famous scheduling algorithm with optimal speedup bound properties. However, when EDF-VD is used to schedule task sets using a model with additional or relaxed constraints, its scheduling properties change. Inspired by an application of MC to the scheduling of fault tolerant tasks, in this article, we propose two models for multiple criticality levels: the first is a specialization of the MC model, and the second is a generalization of it. We then show, via formal proofs and numerical simulations, that the former considerably improves the speedup bound of EDF-VD. Finally, we provide the proofs related to the optimality of the two models, identifying the need of new scheduling algorithms.
2023
ASPDAC '23: Proceedings of the 28th Asia and South Pacific Design Automation Conference
9781450397834
mixed-criticality;real-time;scheduling;fault tolerance
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1222753
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