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A Two-interval Forced-choice Task for Multisensory Comparisons

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Multi-Core Time-Triggered OCBP-Based Scheduling for Mixed Criticality Periodic Task Systems.

Marian D Baciu¹, Eugenia A Capota¹, Cristina S Stângaciu¹

¹Computer and Information Technology Department, Politehnica University Timisoara, V. Parvan 2, 300223 Timisoara, Romania.

Sensors (Basel, Switzerland)

|February 28, 2023

Summary

This study introduces a new scheduling algorithm for mixed criticality systems on multiprocessor platforms. The Partitioned Time-Triggered Own Criticality Based Priority algorithm enhances real-time scheduling in time-triggered environments.

Keywords:

embedded systems mixed criticality systems multiprocessor systems non-preemptive scheduling real-time scheduling time-triggered scheduling

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Area of Science:

Computer Science
Real-Time Systems Engineering
Embedded Systems

Background:

Mixed criticality systems integrate tasks with varying safety and timing requirements.
The complexity of embedded systems necessitates advanced scheduling techniques.
Time-triggered environments offer determinism and isolation, crucial for certification.

Purpose of the Study:

To address the limited research on multiprocessor scheduling for time-triggered mixed criticality systems.
To propose a novel scheduling algorithm for periodic tasks in such environments.
To analyze the performance of the proposed algorithm against existing methods.

Main Methods:

A partitioned, non-preemptive, table-driven scheduling algorithm named Partitioned Time-Triggered Own Criticality Based Priority was developed.
The algorithm is based on a uniprocessor mixed criticality scheduling approach.
Performance analysis involved comparing the algorithm's success ratio against event-driven and time-triggered methods.

Main Results:

The proposed Partitioned Time-Triggered Own Criticality Based Priority algorithm was detailed.
An analysis of the algorithm's success ratio was conducted.
Comparative results against event-driven and other time-triggered methods were presented.

Conclusions:

The research contributes a new scheduling solution for complex mixed criticality systems.
The proposed algorithm offers a deterministic and certifiable approach for multiprocessor platforms.
Further analysis demonstrated its performance characteristics in a time-triggered context.