Two Accepted Papers in RTAS 2023!

I am very delighted to have our papers “Scheduling Periodic Segmented Self-Suspending Tasks without Timing Anomalies” and “Average Task Execution Time Minimization under (m,k) Soft-Error Constraint” accepted for presentation at the upcoming 29th IEEE Real-Time and Embedded Technology and Applications Symposium.

On the first paper, we eliminate timing anomalies without negative impacts on the worst-case response time (WCRT) analysis when scheduling periodic tasks with segmented self-suspension behavior. We propose two treatments, segment release time enforcement and segment priority modification, and prove that both treatments eliminate timing anomalies.

On the second paper, we propose two dynamic (and adaptive) approaches, i.e., Markov Chain based approach and reinforcement learning-based approach, that allow the scheduler to dynamically select execution modes based on the error-history of the past jobs and the actual error probability.

Thanks to the DAES group in TU Dortmund, Germany! See you in San Antonio, Texas!

Kuan-Hsun Chen
Kuan-Hsun Chen
Assistant Professor

In this era, I make computing systems future-proof and future-ready.