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Artykuły w czasopismach na temat "Probabilistic execution time"
Tongsima, S., E. H. M. Sha, C. Chantrapornchai, D. R. Surma i N. L. Passos. "Probabilistic loop scheduling for applications with uncertain execution time". IEEE Transactions on Computers 49, nr 1 (2000): 65–80. http://dx.doi.org/10.1109/12.822565.
Pełny tekst źródłaDraskovic, Stefan, Rehan Ahmed, Pengcheng Huang i Lothar Thiele. "Schedulability of probabilistic mixed-criticality systems". Real-Time Systems 57, nr 4 (21.02.2021): 397–442. http://dx.doi.org/10.1007/s11241-021-09365-4.
Pełny tekst źródłaSantos, R., J. Santos i J. Orozco. "Hard Real-Time Systems with Stochastic Execution Times: Deterministic and Probabilistic Guarantees". International Journal of Computers and Applications 27, nr 2 (styczeń 2005): 57–62. http://dx.doi.org/10.1080/1206212x.2005.11441758.
Pełny tekst źródłaJimenez Gil, Samuel, Iain Bate, George Lima, Luca Santinelli, Adriana Gogonel i Liliana Cucu-Grosjean. "Open Challenges for Probabilistic Measurement-Based Worst-Case Execution Time". IEEE Embedded Systems Letters 9, nr 3 (wrzesień 2017): 69–72. http://dx.doi.org/10.1109/les.2017.2712858.
Pełny tekst źródłaXiao, Peng, Dongbo Liu i Kaijian Liang. "Improving scheduling efficiency by probabilistic execution time model in cloud environments". International Journal of Networking and Virtual Organisations 18, nr 4 (2018): 307. http://dx.doi.org/10.1504/ijnvo.2018.093651.
Pełny tekst źródłaXiao, Peng, Dongbo Liu i Kaijian Liang. "Improving scheduling efficiency by probabilistic execution time model in cloud environments". International Journal of Networking and Virtual Organisations 18, nr 4 (2018): 307. http://dx.doi.org/10.1504/ijnvo.2018.10014681.
Pełny tekst źródłaRen, Jiankang, Zichuan Xu, Chao Yu, Chi Lin, Guowei Wu i Guozhen Tan. "Execution allowance based fixed priority scheduling for probabilistic real-time systems". Journal of Systems and Software 152 (czerwiec 2019): 120–33. http://dx.doi.org/10.1016/j.jss.2019.03.001.
Pełny tekst źródłaLacerda, Bruno, David Parker i Nick Hawes. "Multi-Objective Policy Generation for Mobile Robots under Probabilistic Time-Bounded Guarantees". Proceedings of the International Conference on Automated Planning and Scheduling 27 (5.06.2017): 504–12. http://dx.doi.org/10.1609/icaps.v27i1.13865.
Pełny tekst źródłaChanel, Caroline, Charles Lesire i Florent Teichteil-Königsbuch. "A Robotic Execution Framework for Online Probabilistic (Re)Planning". Proceedings of the International Conference on Automated Planning and Scheduling 24 (11.05.2014): 454–62. http://dx.doi.org/10.1609/icaps.v24i1.13669.
Pełny tekst źródłaFusi, Matteo, Fabio Mazzocchetti, Albert Farres, Leonidas Kosmidis, Ramon Canal, Francisco J. Cazorla i Jaume Abella. "On the Use of Probabilistic Worst-Case Execution Time Estimation for Parallel Applications in High Performance Systems". Mathematics 8, nr 3 (1.03.2020): 314. http://dx.doi.org/10.3390/math8030314.
Pełny tekst źródłaRozprawy doktorskie na temat "Probabilistic execution time"
Küttler, Martin, Michael Roitzsch, Claude-Joachim Hamann i Marcus Völp. "Probabilistic Analysis of Low-Criticality Execution". Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-233117.
Pełny tekst źródłaKüttler, Martin, Michael Roitzsch, Claude-Joachim Hamann i Marcus Völp. "Probabilistic Analysis of Low-Criticality Execution". Technische Universität Dresden, 2017. https://tud.qucosa.de/id/qucosa%3A30798.
Pełny tekst źródłaKumar, Tushar. "Characterizing and controlling program behavior using execution-time variance". Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/55000.
Pełny tekst źródłaGuet, Fabrice. "Étude de l'application de la théorie des valeurs extrêmes pour l'estimation fiable et robuste du pire temps d'exécution probabiliste". Thesis, Toulouse, ISAE, 2017. http://www.theses.fr/2017ESAE0041/document.
Pełny tekst źródłaSoftware tasks are time constrained in real time computing systems. To ensure the safety of the critical systems that embeds the real time system, it is of paramount importance to safely estimate the worst-case execution time of each task. Modern commercial processors optimisation components enable to reduce in average the task execution time at the cost of a hard to determine task worst-case execution time. Many approaches for executing a task worst-case execution time exist but are usually segregated and hardly scalable, or by building very complex models. Measurement-based probabilistic timing analysis approaches are said to be easy and fast, but they suffer from a lack of systematism and confidence in their estimates. This thesis studies the applicability of the extreme value theory to a sequence of execution time measurements for the estimation of the probabilistic worst-case execution time, leading to the development of the diagxtrm tool. Thanks to a large panel of sequences of measurements from different real time systems, capabilities and limits of the tool are enlightened. Finally, a couple of methods are provided for determining measurements conditions that foster the application of the theory and raise more confidence in the estimates
Części książek na temat "Probabilistic execution time"
Guan, Ji, i Nengkun Yu. "A Probabilistic Logic for Verifying Continuous-time Markov Chains". W Tools and Algorithms for the Construction and Analysis of Systems, 3–21. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99527-0_1.
Pełny tekst źródłaMeyer, Philipp J., Javier Esparza i Philip Offtermatt. "Computing the Expected Execution Time of Probabilistic Workflow Nets". W Tools and Algorithms for the Construction and Analysis of Systems, 154–71. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17465-1_9.
Pełny tekst źródłaSantinelli, Luca, i Zhishan Guo. "On the Criticality of Probabilistic Worst-Case Execution Time Models". W Dependable Software Engineering. Theories, Tools, and Applications, 59–74. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69483-2_4.
Pełny tekst źródłaReghenzani, Federico. "Beyond the Traditional Analyses and Resource Management in Real-Time Systems". W Special Topics in Information Technology, 67–77. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85918-3_6.
Pełny tekst źródłaLundén, Daniel, Gizem Çaylak, Fredrik Ronquist i David Broman. "Automatic Alignment in Higher-Order Probabilistic Programming Languages". W Programming Languages and Systems, 535–63. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30044-8_20.
Pełny tekst źródłaHöfig, Kai. "Failure-Dependent Timing Analysis - A New Methodology for Probabilistic Worst-Case Execution Time Analysis". W Lecture Notes in Computer Science, 61–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28540-0_5.
Pełny tekst źródłaStemmer, Ralf, Hai-Dang Vu, Kim Grüttner, Sebastien Le Nours, Wolfgang Nebel i Sebastien Pillement. "Experimental Evaluation of Probabilistic Execution-Time Modeling and Analysis Methods for SDF Applications on MPSoCs". W Lecture Notes in Computer Science, 241–54. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27562-4_17.
Pełny tekst źródłaFalcone, Yliès, Gwen Salaün i Ahang Zuo. "Probabilistic Runtime Enforcement of Executable BPMN Processes". W Fundamental Approaches to Software Engineering, 56–76. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57259-3_3.
Pełny tekst źródłaGentili, Elisabetta, Alice Bizzarri, Damiano Azzolini, Riccardo Zese i Fabrizio Riguzzi. "Regularization in Probabilistic Inductive Logic Programming". W Inductive Logic Programming, 16–29. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-49299-0_2.
Pełny tekst źródłaHuang, Wei-Chih, i William J. Knottenbelt. "Low-Overhead Development of Scalable Resource-Efficient Software Systems". W Advances in Systems Analysis, Software Engineering, and High Performance Computing, 81–105. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6026-7.ch005.
Pełny tekst źródłaStreszczenia konferencji na temat "Probabilistic execution time"
Liang, Yun, i Tulika Mitra. "Cache modeling in probabilistic execution time analysis". W the 45th annual conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1391469.1391551.
Pełny tekst źródłaArcaro, Luis Fernando, Karila Palma Silva, Romulo Silva de Oliveira i Luis Almeida. "Reliability Test based on a Binomial Experiment for Probabilistic Worst-Case Execution Times". W 2020 IEEE Real-Time Systems Symposium (RTSS). IEEE, 2020. http://dx.doi.org/10.1109/rtss49844.2020.00016.
Pełny tekst źródłaZhu, Dakai, Hakan Aydin i Jian-Jia Chen. "Optimistic Reliability Aware Energy Management for Real-Time Tasks with Probabilistic Execution Times". W 2008 IEEE 29th Real-Time Systems Symposium (RTSS). IEEE, 2008. http://dx.doi.org/10.1109/rtss.2008.37.
Pełny tekst źródłaHardy, Damien, i Isabelle Puaut. "Static probabilistic worst case execution time estimation for architectures with faulty instruction caches". W the 21st International conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2516821.2516842.
Pełny tekst źródłaMarchiori, Dúnia, Ricardo Custódio, Daniel Panario i Lucia Moura. "Towards constant-time probabilistic root finding for code-based cryptography". W Simpósio Brasileiro de Segurança da Informação e de Sistemas Computacionais. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/sbseg.2021.17313.
Pełny tekst źródłaMarchiori, Dúnia, Ricardo Custódio, Daniel Panario i Lucia Moura. "Towards constant-time probabilistic root finding for code-based cryptography". W Simpósio Brasileiro de Segurança da Informação e de Sistemas Computacionais. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/sbseg.2021.17313.
Pełny tekst źródłaPsarros, George Ad. "Comparing the Navigator’s Response Time in Collision and Grounding Accidents". W ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/omae2015-41001.
Pełny tekst źródłaSaint-Guillain, Michael, Tiago Stegun Vaquero, Jagriti Agrawal i Steve Chien. "Robustness Computation of Dynamic Controllability in Probabilistic Temporal Networks with Ordinary Distributions". W Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/576.
Pełny tekst źródłaOrji, Mirian Kosi, Toyin Arowosafe i John Agiaye. "Improving Well Construction/Intervention Time and Cost Estimation Accuracy Via Historical Performance Data Analysis". W SPE Nigeria Annual International Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/217196-ms.
Pełny tekst źródłaMohamat Nor, Noor Azman, i Andrew Findlay. "Unit Health Assessment- Oil & Gas Equipment Probabilistic Case Study". W ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/gt2021-59318.
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