Dynamic Scheduling Strategies for Firm Semi-Periodic Real-Time Tasks - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Computers Année : 2023

Dynamic Scheduling Strategies for Firm Semi-Periodic Real-Time Tasks

Résumé

This paper introduces and assesses novel strategies to schedule firm semi-periodic real-time tasks. Jobs are released periodically and have the same relative deadline. Job execution times obey an arbitrary probability distribution and can take either bounded or unbounded values. We investigate several optimization criteria, the most prominent being the Deadline Miss Ratio (DMR). All previous work uses some admission policies but never interrupt the execution of an admitted job before its deadline. On the contrary, we introduce three new control parameters to dynamically decide whether to interrupt a job at any given time. We derive a Markov model and use its stationary distribution to determine the best value of each control parameter. Finally we conduct an extensive simulation campaign with 16 different probability distributions. The results nicely demonstrate how the new strategies help improve system performance compared with traditional approaches. In particular, we show that (i) compared to pre-execution admission rules, the control parameters make significantly better decisions; (ii) specifically, the key control parameter is to upper bound the waiting time of each job; (iii) the best scheduling strategy decreases the DMR by up to 0.35 over traditional competitors.
Fichier principal
Vignette du fichier
revised_ieeetc_submitted_June_15_2022.pdf (1.58 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03778357 , version 1 (15-09-2022)
hal-03778357 , version 2 (21-09-2022)

Identifiants

Citer

Yiqin Gao, Guillaume Pallez, Yves Robert, Frédéric Vivien. Dynamic Scheduling Strategies for Firm Semi-Periodic Real-Time Tasks. IEEE Transactions on Computers, 2023, 72 (1), pp.55-68. ⟨10.1109/TC.2022.3208203⟩. ⟨hal-03778357v2⟩
85 Consultations
123 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More