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Department of Computer Science
SUS-AWARE

Suspension-Aware Design and Analysis

In computing systems, a job may suspend itself, due to the interactions with external I/O devices or accelerators, multicore systems with shared resources, suspension-aware multiprocessor synchronization protocols, etc. For real-time embedded systems, self-suspension behavior negatively impact the schedulability of real-time tasks and typically cause substantial performance/schedulability degradation.

Fig: Two tasks τ1 (higher priority, period 5, relative deadline 5, computation time 3) and τ2 (lower priority, period 7, relative deadline 7, computation time 2) meet their deadlines in (a). Conventional schedulability analysis predicts maximum response times of 3 and 5 respectively. In (b), task τ1 suspends itself, with the result that task τ2 misses its deadline at time 14.  (Source: Many suspensions many problems by Chen et al. in RTSJ 2019)

Even though some seemingly positive results have been reported for tackling self-suspending task systems in the past, the recent investigation by Prof. Dr. Jian-Jia Chen and his colleagues indicates that a significant portion of the literature (and also the majority of these results) before 2013 has been seriously flawed. Since most results before 2013 were in fact flawed (or with incomplete proofs), the investigation of self-suspending task models in real-time embedded systems has been restarted since 2015.

This project intends to investigate robust and solid fundamental algorithms and analyses to carefully mitigate (via safe and sound execution/suspension enforcements) and analyze (via tight schedulability tests) the impact of self-suspending behavior in modern real-time embedded systems. The targeting systems are safety-critical systems with real-time requirements. Since the self-suspending behavior can introduce a high degree of complexity, new scheduling strategies or revisions of existing scheduling strategies are required. This project intends to provide fundamental breakthrough in the scheduling theory and the corresponding schedulability analysis to flexibly accommodate the self-suspension behavior without introducing much pessimism when considering the worst-case timing behavior.

With the scheduling strategies and schedulability tests provided in this project, we aim to offer tools for real-time system designers so that further optimizations by considering the perspectives of controllers, communications, and computation are possible.

(Source: DFG)

Project Information

Duration: Nov. 2019 - Oct. 2022 (3 years)
Resources:
  • Jian-Jia Chen, Geoffrey Nelissen, Wen-Hung Huang, Maolin Yang, Björn B. Brandenburg, Konstantinos Bletsas, Cong Liu, Pascal Richard, Frédéric Ridouard, Neil C. Audsley, Raj Rajkumar, Dionisio de Niz, Georg von der Brüggen: Many suspensions, many problems: a review of self-suspending tasks in real-time systems. Real-Time Systems 55(1): 144-207 (2019). Open Access Download
  • Jian-Jia Chen, Georg von der Brüggen, Wen-Hung Huang, Cong Liu:State of the art for scheduling and analyzing self-suspending sporadic real-time tasks. RTCSA 2017: 1-10. IEEE Xplore Link
Hired: M.Sc. Mario Günzel

Publications

2023
2022
2021
2020
2019

Tools

  • https://github.com/tu-dortmund-ls12-rt/SSSEvaluation
  • Correspodning paper can be found in "Work-in-Progress: Evaluation Framework for Self-Suspending Schedulability Tests" by Mario Günzel, Harun Teper, Kuan-Hsun Chen, Georg von der Brüggen, and Jian-Jia Chen, IEEE Real-Time Sys­tems Symposium (RTSS),  pp 532-535, 2021

 

© tu-dortmund-ls12-rt on github

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