PhD Thesis: Beyond the Traditional Analyses and Resource Management in Real-Time Systems
Creators: name: Reghenzani, Federico
Publisher: name: Zenodo
Year: 2021
Subjects: real-time computing
pwcet
resource management

description: Estimating the worst-case execution time in modern architecture is a non-trivial problem. The presence of complex hardware features, necessary to improve the computational power due to the single-core performance barrier, makes this estimation difficult or even impossible if traditional techniques are employed. Probabilistic real-time and, in particular, the measurement-based probabilistic timing analysis have been developed to overcome this issue. Measurement-based approaches are very appealing for the industrial world, because they enable to obtain a statistical estimation of the worst-case execution time by directly observing the execution time of the real system. Unfortunately, the current status of probabilistic real-time is far to be acceptable for certification purposes of safety-critical systems. In this thesis, both theoretical and experimental works, related to the PhD activities, are presented, with a special focus on the uncertainty estimation and the applicability of the probabilistic real-time techniques to real platforms. Both these problems have been studied, providing theoretical tools and experimental evaluations to advance probabilistic approaches towards a safe solution to the worst-case execution time estimation problem. The issues, which still limit the use of such techniques in industrial environment, are discussed and possible future research directions presented. In addition, unconventional exploitations of probabilistic real-time are proposed for mixed-criticality, high performance computing, and energy-constrained systems. During all of these works, some software tools and datasets have been developed, released as open-source and described in this thesis.
description: {"references": ["L. Premi, F. Reghenzani, G. Massari, and W. Fornaciari. A Game Theory Approach to Heterogeneous Resource Management. In 2020 International Conference on Embedded Software, 2020.", "F. Reghenzani, G. Massari, and W. Fornaciari. Mixed Time-Criticality Process Interferences Characterization on a Multicore Linux System. In 2017 Euromi- cro Conference on Digital System Design (DSD), pages 427\u2013434, 2017. doi: 10.1109/DSD.2017.18.", "F. Reghenzani, G. Massari, and W. Fornaciari. chronovise: Measurement-Based Probabilistic Timing Analysis framework. Journal of Open Source Software, 3(28):711, 2018. doi: 10.21105/joss.00711.", "F. Reghenzani, G. Massari, and W. Fornaciari. A Probabilistic Approach to Energy- Constrained Mixed-Criticality Systems. In 2019 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), pages 1\u20136, 2019.", "F. Reghenzani, G. Massari, and W. Fornaciari. The Real-Time Linux Kernel: A Survey on PREEMPT_RT. ACM Comput. Surv., 52(1):18:1\u201318:36, February 2019. ISSN 0360-0300. doi: 10.1145/3297714.", "F. Reghenzani, G. Massari, and W. Fornaciari. The Misconception of Exponential Tail Upper-Bounding in Probabilistic Real Time. IEEE Embedded Systems Letters, 11(3):77\u2013 80, 2019.", "F. Reghenzani, G. Massari, W. Fornaciari, and A. Galimberti. Probabilistic-WCET Re- liability: On the Experimental Validation of EVT Hypotheses. In Int. Conf. on Omni- Layer Intelligent Systems, COINS, pages 229\u2013234. ACM, 2019. ISBN 978-1-4503-6640- 3. doi: 10.1145/3312614.3312660.", "F. Reghenzani, G. Massari, L. Santinelli, and W. Fornaciari. Statistical power estimation dataset for external validation GoF tests on EVT distribution. Data in Brief, 25:104071, 2019. ISSN 2352-3409. doi: 10.1016/j.dib.2019.104071.", "F. Reghenzani, L. Santinelli, and W. Fornaciari. Why Statistical Power Mat- ters for Probabilistic Real-Time: Work-in-Progress. In Proceedings of the Interna- tional Conference on Embedded Software Companion, EMSOFT '19, New York, NY, USA, 2019. Association for Computing Machinery. ISBN 9781450369244. doi: 10.1145/3349568.3351555.", "F. Reghenzani, G. Massari, and W. Fornaciari. Probabilistic Predictability Index MATLAB Script, January 2020. Zenodo. doi: 10.5281/zenodo.3596957.", "F. Reghenzani, G. Massari, and W. Fornaciari. Probabilistic-WCET reliability: Statistical testing of EVT hypotheses. Microprocessors and Microsystems, 77:103135, 2020. ISSN 0141-9331. doi: 10.1016/j.micpro.2020.103135.", "F. Reghenzani, G. Massari, and W. Fornaciari. Timing predictability in high-performance computing with probabilistic real-time. IEEE Access, 8:208566\u2013208582, 2020. doi: 10.1109/ACCESS.2020.3038559.", "F. Reghenzani, L. Santinelli, and W. Fornaciari. Dealing with Uncertainty in pWCET Estimations. ACM Trans. Embed. Comput. Syst. (TECS), 19(5), 2020. ISSN 1539-9087. doi: 10.1145/3396234."]}