Literatura científica selecionada sobre o tema "Probabilistic execution time"
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Artigos de revistas sobre o assunto "Probabilistic execution time"
Tongsima, S., E. H. M. Sha, C. Chantrapornchai, D. R. Surma e N. L. Passos. "Probabilistic loop scheduling for applications with uncertain execution time". IEEE Transactions on Computers 49, n.º 1 (2000): 65–80. http://dx.doi.org/10.1109/12.822565.
Texto completo da fonteDraskovic, Stefan, Rehan Ahmed, Pengcheng Huang e Lothar Thiele. "Schedulability of probabilistic mixed-criticality systems". Real-Time Systems 57, n.º 4 (21 de fevereiro de 2021): 397–442. http://dx.doi.org/10.1007/s11241-021-09365-4.
Texto completo da fonteSantos, R., J. Santos e J. Orozco. "Hard Real-Time Systems with Stochastic Execution Times: Deterministic and Probabilistic Guarantees". International Journal of Computers and Applications 27, n.º 2 (janeiro de 2005): 57–62. http://dx.doi.org/10.1080/1206212x.2005.11441758.
Texto completo da fonteJimenez Gil, Samuel, Iain Bate, George Lima, Luca Santinelli, Adriana Gogonel e Liliana Cucu-Grosjean. "Open Challenges for Probabilistic Measurement-Based Worst-Case Execution Time". IEEE Embedded Systems Letters 9, n.º 3 (setembro de 2017): 69–72. http://dx.doi.org/10.1109/les.2017.2712858.
Texto completo da fonteXiao, Peng, Dongbo Liu e Kaijian Liang. "Improving scheduling efficiency by probabilistic execution time model in cloud environments". International Journal of Networking and Virtual Organisations 18, n.º 4 (2018): 307. http://dx.doi.org/10.1504/ijnvo.2018.093651.
Texto completo da fonteXiao, Peng, Dongbo Liu e Kaijian Liang. "Improving scheduling efficiency by probabilistic execution time model in cloud environments". International Journal of Networking and Virtual Organisations 18, n.º 4 (2018): 307. http://dx.doi.org/10.1504/ijnvo.2018.10014681.
Texto completo da fonteRen, Jiankang, Zichuan Xu, Chao Yu, Chi Lin, Guowei Wu e Guozhen Tan. "Execution allowance based fixed priority scheduling for probabilistic real-time systems". Journal of Systems and Software 152 (junho de 2019): 120–33. http://dx.doi.org/10.1016/j.jss.2019.03.001.
Texto completo da fonteLacerda, Bruno, David Parker e 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 de junho de 2017): 504–12. http://dx.doi.org/10.1609/icaps.v27i1.13865.
Texto completo da fonteChanel, Caroline, Charles Lesire e Florent Teichteil-Königsbuch. "A Robotic Execution Framework for Online Probabilistic (Re)Planning". Proceedings of the International Conference on Automated Planning and Scheduling 24 (11 de maio de 2014): 454–62. http://dx.doi.org/10.1609/icaps.v24i1.13669.
Texto completo da fonteFusi, Matteo, Fabio Mazzocchetti, Albert Farres, Leonidas Kosmidis, Ramon Canal, Francisco J. Cazorla e Jaume Abella. "On the Use of Probabilistic Worst-Case Execution Time Estimation for Parallel Applications in High Performance Systems". Mathematics 8, n.º 3 (1 de março de 2020): 314. http://dx.doi.org/10.3390/math8030314.
Texto completo da fonteTeses / dissertações sobre o assunto "Probabilistic execution time"
Küttler, Martin, Michael Roitzsch, Claude-Joachim Hamann e 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.
Texto completo da fonteKüttler, Martin, Michael Roitzsch, Claude-Joachim Hamann e Marcus Völp. "Probabilistic Analysis of Low-Criticality Execution". Technische Universität Dresden, 2017. https://tud.qucosa.de/id/qucosa%3A30798.
Texto completo da fonteKumar, Tushar. "Characterizing and controlling program behavior using execution-time variance". Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/55000.
Texto completo da fonteGuet, 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.
Texto completo da fonteSoftware 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
Capítulos de livros sobre o assunto "Probabilistic execution time"
Guan, Ji, e Nengkun Yu. "A Probabilistic Logic for Verifying Continuous-time Markov Chains". In 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.
Texto completo da fonteMeyer, Philipp J., Javier Esparza e Philip Offtermatt. "Computing the Expected Execution Time of Probabilistic Workflow Nets". In 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.
Texto completo da fonteSantinelli, Luca, e Zhishan Guo. "On the Criticality of Probabilistic Worst-Case Execution Time Models". In 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.
Texto completo da fonteReghenzani, Federico. "Beyond the Traditional Analyses and Resource Management in Real-Time Systems". In Special Topics in Information Technology, 67–77. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85918-3_6.
Texto completo da fonteLundén, Daniel, Gizem Çaylak, Fredrik Ronquist e David Broman. "Automatic Alignment in Higher-Order Probabilistic Programming Languages". In Programming Languages and Systems, 535–63. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30044-8_20.
Texto completo da fonteHöfig, Kai. "Failure-Dependent Timing Analysis - A New Methodology for Probabilistic Worst-Case Execution Time Analysis". In 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.
Texto completo da fonteStemmer, Ralf, Hai-Dang Vu, Kim Grüttner, Sebastien Le Nours, Wolfgang Nebel e Sebastien Pillement. "Experimental Evaluation of Probabilistic Execution-Time Modeling and Analysis Methods for SDF Applications on MPSoCs". In Lecture Notes in Computer Science, 241–54. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27562-4_17.
Texto completo da fonteFalcone, Yliès, Gwen Salaün e Ahang Zuo. "Probabilistic Runtime Enforcement of Executable BPMN Processes". In Fundamental Approaches to Software Engineering, 56–76. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57259-3_3.
Texto completo da fonteGentili, Elisabetta, Alice Bizzarri, Damiano Azzolini, Riccardo Zese e Fabrizio Riguzzi. "Regularization in Probabilistic Inductive Logic Programming". In Inductive Logic Programming, 16–29. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-49299-0_2.
Texto completo da fonteHuang, Wei-Chih, e William J. Knottenbelt. "Low-Overhead Development of Scalable Resource-Efficient Software Systems". In 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.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Probabilistic execution time"
Liang, Yun, e Tulika Mitra. "Cache modeling in probabilistic execution time analysis". In the 45th annual conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1391469.1391551.
Texto completo da fonteArcaro, Luis Fernando, Karila Palma Silva, Romulo Silva de Oliveira e Luis Almeida. "Reliability Test based on a Binomial Experiment for Probabilistic Worst-Case Execution Times". In 2020 IEEE Real-Time Systems Symposium (RTSS). IEEE, 2020. http://dx.doi.org/10.1109/rtss49844.2020.00016.
Texto completo da fonteZhu, Dakai, Hakan Aydin e Jian-Jia Chen. "Optimistic Reliability Aware Energy Management for Real-Time Tasks with Probabilistic Execution Times". In 2008 IEEE 29th Real-Time Systems Symposium (RTSS). IEEE, 2008. http://dx.doi.org/10.1109/rtss.2008.37.
Texto completo da fonteHardy, Damien, e Isabelle Puaut. "Static probabilistic worst case execution time estimation for architectures with faulty instruction caches". In the 21st International conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2516821.2516842.
Texto completo da fonteMarchiori, Dúnia, Ricardo Custódio, Daniel Panario e Lucia Moura. "Towards constant-time probabilistic root finding for code-based cryptography". In 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.
Texto completo da fonteMarchiori, Dúnia, Ricardo Custódio, Daniel Panario e Lucia Moura. "Towards constant-time probabilistic root finding for code-based cryptography". In 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.
Texto completo da fontePsarros, George Ad. "Comparing the Navigator’s Response Time in Collision and Grounding Accidents". In 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.
Texto completo da fonteSaint-Guillain, Michael, Tiago Stegun Vaquero, Jagriti Agrawal e Steve Chien. "Robustness Computation of Dynamic Controllability in Probabilistic Temporal Networks with Ordinary Distributions". In 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.
Texto completo da fonteOrji, Mirian Kosi, Toyin Arowosafe e John Agiaye. "Improving Well Construction/Intervention Time and Cost Estimation Accuracy Via Historical Performance Data Analysis". In SPE Nigeria Annual International Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/217196-ms.
Texto completo da fonteMohamat Nor, Noor Azman, e Andrew Findlay. "Unit Health Assessment- Oil & Gas Equipment Probabilistic Case Study". In 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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