Using machine learning for multiprocessor real-time systems scheduling analysis

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

Authors

Publication Details

Journal
International Journal of Electronic Security and Digital Forensics
Published
2024-12-22
DOI
https://doi.org/10.1504/ijesdf.2026.10068575
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

Using machine learning for multiprocessor real-time systems scheduling analysis

Walid Karamti, Lubna Sawaf
International Journal of Electronic Security and Digital Forensics
Scheduling and Optimization Algorithms
article

Using machine learning for multiprocessor real-time systems scheduling analysis

Walid Karamti, Lubna Sawaf
article en

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

International Journal of Electronic Security and Digital ForensicsVol. 1(1)
Openalex Percentile: Top 65%
Scheduling and Optimization Algorithms
DOIOpen Access PDFOpenAlex
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Using machine learning for multiprocessor real-time systems scheduling analysis — Walid Karamti, Lubna Sawaf · International Journal of Electronic Security and Digital Forensics (2024) | TGRS Research Map | TGRS