Reconstruction of the execution times dynamics of real-time tasks by fuzzy digital filtering
DOI:
https://doi.org/10.17533/udea.redin.14002Keywords:
execution time, estimator, fuzzy filtering, reconstruction, real-time taskAbstract
Real-time systems (RTS) process their activities through tasks which in turn consist of a set of instances, each one of this real-time task (RTT) have six temporary constraints: arrival time, start time, execution time, end time, over time and deadline. Of these six constraints, the execution time depends directly on the software and hardware of the computer, because of that this temporary constraints varies due to external and internal factors, this variation may cause at least some instance does not satisfy the deadline, in this sense it is important to propose a model to reconstruct the behavior of the execution times for the purpose to determine the proportions of the Real-time System, propose appropriate techniques of fault tolerance and improve operating modules. Therefore in this paper, is proposed a model to reconstruct the execution times from measurements made at a program algorithm developed in the real-time operating system QNX Neutrino 6.5. This reconstruction is done by a model type autoregressive–moving-average integrated with parameter estimator constructed with a digital filtering procedure diffuse (FDD). To validate the reconstruction is used the mean square error which converges to a region close to zero and indicate that the reconstruction is good.
Downloads
References
J. Medel, P. Guevara, D. Cruz. “Temas selectos de sistemas en tiempo real.” Tareas en Tiempo Real. 1a ed. Ed. Politécnico. México DF., México. 2007. pp.50- 54
S. Manolache, P. Eles, Z. Peng. “Schedulability Analysis of Applications with Stochastic Task Execution Times”. ACM Trans. on Embedded Computing Systems. Vol. 3. 2004. pp. 706-735. DOI: https://doi.org/10.1145/1027794.1027797
F. Stappert, P. Altenbernd. “Complete Worst-Case Execution Time Analysis of Straight-line Hard RealTime Programs”. Journal of Systems Architecture. Vol. 46. 2000. pp. 339-355. DOI: https://doi.org/10.1016/S1383-7621(99)00010-7
G. Bernat, A. Colin, S. Petters. pWCET: A tool for probabilistic Worst-Case Execution Time Analysis of Real-Time Systems. Technical Report YCS-2003-353. Department of Computer Science, University of York. York, UK. 2003. pp. 1-18.
P. Guevara, J. Medel, G. Delgado. “Description of execution time dynamics for a set of concurrent real-time tasks”. Revista Facultad de Ingeniería: Universidad de Antioquía. Nº. 61. 2011. pp. 123-131.
T. Söderström, P. Stoica. “On some system identification techniques for adaptive filtering”. IEEE Trans. Circuits and Systems. Vol. 35. 1988. pp. 457- 461. DOI: https://doi.org/10.1109/31.1765
J. Medel, P. Guevara, D. Cruz. Matricial estimation for start times with stochastic behavior by periodic real time tasks in a concurrent system. Proc. of the 7th International Conference on Mathematical Methods and Computational Techniques In Electrical Engineering. Sofia, Bulgaria. 2005. pp. 214-217.
C. Liu, J. Layland. “Scheduling algorithms for multiprogramming in hard-real-time environment”. Journal of the ACM, Vol. 20. 1973. pp. 273-250. DOI: https://doi.org/10.1145/321738.321743
P. Felix “Fuzzy Temporal Profiles: A Model for the representation and Recognition of signal patterns”. Computación y Sistemas. Vol. 4. 2001. pp. 385-388.
L. Di Lascio, E. Fischetti, A. Gisolfi. “Fuzzy Modeling and Evaluation of an IMTS User”. Computación y Sistemas. Vol. 5. 2002. pp. 247-255.
M. Chacón “A Fuzzy Neural Netwotk Approach for Document Region Classification Using Human Visual Perception Features”. Computación y Sistemas. Vol. 6. 2002. pp. 083-093.
M. Chacón, A. Corral, R. Sandoval. “A Fuzzy Approach on Image Complexity Measure”. Computación y Sistemas. Vol. 10. 2007. pp. 268-284
J. Aguilar. “Dynamic Random Fuzzy Cognitive Maps”. Computación y Sistemas. Vol. 7. 2004. pp. 260-270.
E. Gorrostieta, E. Vargas. “Algoritmo Difuso de Locomoción Libre para un Robot Caminante de Seis Patas”. Computación y Sistemas. Vol. 11. 2008. pp. 260-287.
C. López, C. Yáñez, A. Gutiérrez, E. Felipe. “Adequacy Checking of Personal Software Development Effort Estimation Models Based upon Fuzzy logic: A Replicated Experiment”. Computación y Sistemas. Vol. 11. 2008. pp. 333-348.
J. García. “Filtrado Digital Difuso en Tiempo real”. Computación y Sistemas. Vol. 11. 2008. pp. 390-401.
J. García, J. Medel, P.Guevara. “Filtrado Difuso en Tiempo Real”. Computación y Sistemas. Vol. 11. 2008. pp. 390-401.
J. Medel, J. García, J. Sánchez. “Real-time Fuzzy Digital Filters (RTFDF) Properties for SISO Systems”. Automatic Control and Computer Sciences. Vol. 42. 2008. pp. 26-34. DOI: https://doi.org/10.3103/S0146411608010045
J. García, J. Medel, J. Sánchez. “Filtrado Neuronal Difuso: Caso MIMO”. Revista Ingeniería e Investigación. Vol. 31. 2011. pp. 184-192. DOI: https://doi.org/10.15446/ing.investig.v31n1.20569
J. Valdez, C. García, P. Guevara, J. Sánchez. Filtrado Difuso para la reconstrucción de la dinámica de tiempos de ejecución para n instancias en una tarea en tiempo real. Memorias del CIINDET 2011. Morelos, México. 2011. pp. 1-8.
S. Vázquez, J. García, J. Sánchez. Descripción del Filtrado Adaptativo Difuso en un DSK TMS320C6713. Memorias del CIINDET 2009. Morelos, México. 2009. pp. 1-6.
G. Delgado, P. Guevara, J. Falcón. Simulación Concurrente en Tiempo Real de un motor de Corriente Continua Sobre la Plataforma QNX. Memorias del XIV Congreso Latinoamericano de Control Automático, XIX Congreso de la Asociación Chilena de Control Automático ACCA. Santiago de Chile, Chile. 2010. pp. 1-6.
R. Krten. QNX Neutrino RTOS Getting Started with QNX Neutrino: A Guide for Real-time Programmers. 1a ed. Ed. QNX Software Systems International Corporation. Canada. 2008. pp. 191-283.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2018 Revista Facultad de Ingeniería
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Revista Facultad de Ingeniería, Universidad de Antioquia is licensed under the Creative Commons Attribution BY-NC-SA 4.0 license. https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en
You are free to:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
Under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
The material published in the journal can be distributed, copied and exhibited by third parties if the respective credits are given to the journal. No commercial benefit can be obtained and derivative works must be under the same license terms as the original work.
Twitter