APPLICATION OF THE REAL-TIME FAN SCHEDULING IN THE EXPLORATION-EXPLOITATION TO OPTIMIZE MINIMUM FUNCTIONS OBJECTIVES

Mariano LARIOS

mariano.larios@correo.buap.mx
Benemérita Universidad Autónoma de Puebla (Mexico)
https://orcid.org/0000-0002-2089-0608

Perfecto M. QUINTERO-FLORES


Universidad Autónoma de Tlaxcala (Facultad de Ciencias Básicas, Ingeniería y Tecnología), México (Mexico)

Mario ANZURES-GARCÍA


Benemérita Universidad Autónoma de Puebla (Facultad de Ciencias de la Computación), México (Mexico)
https://orcid.org/0000-0001-6138-3226

Miguel CAMACHO-HERNANDEZ


Benemérita Universidad Autónoma de Puebla (Facultad de Ciencias de la Computación), México,  (Mexico)
https://orcid.org/0009-0002-8627-9876

Abstract

This paper presents the application of a task scheduling algorithm called Fan on an artificial intelligence technique as genetic algorithms for the problem of finding minima in objective functions, where the equations are predefined to measure the return on an investment. This work combines the methodologies of exploration and exploitation of a population, obtaining results with good aptitudes until finding a better learning based on conditions of not ending until an individual delivers a better aptitude, complying with the established restrictions, exhausting all possible options and fulfilling a stop condition. A real-time task planning algorithm was applied based on consensus techniques. A software tool was developed, and the scheduler called FAN was adapted that contemplates the execution of periodic, aperiodic, and sporadic tasks focused on controlled environments, considering that strict time restrictions are met. In the first phase of the work, it is shown how convergence precipitates to an evolution, this is done in few iterations. In a second stage, exploitation was improved, giving the algorithm a better performance in convergence and feasibility. As a result, there is the exploitation of the population and applying iterations with the fan algorithm and better aptitudes were obtained that occur through asynchronized processes under real-time planning concurrently.

Supporting Agencies

Benemérita Universidad Autónoma de Puebla Mexico

Keywords:

Real-time task scheduling, Genetic algorithms, Concurrent computing

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Published
2023-06-30

Cited by

LARIOS, M., M. QUINTERO-FLORES , P., ANZURES-GARCÍA , M. ., & CAMACHO-HERNANDEZ , M. . (2023). APPLICATION OF THE REAL-TIME FAN SCHEDULING IN THE EXPLORATION-EXPLOITATION TO OPTIMIZE MINIMUM FUNCTIONS OBJECTIVES. Applied Computer Science, 19(2), 43–54. https://doi.org/10.35784/acs-2023-13

Authors

Mariano LARIOS 
mariano.larios@correo.buap.mx
Benemérita Universidad Autónoma de Puebla Mexico
https://orcid.org/0000-0002-2089-0608

Authors

Perfecto M. QUINTERO-FLORES  

Universidad Autónoma de Tlaxcala (Facultad de Ciencias Básicas, Ingeniería y Tecnología), México Mexico

Authors

Mario ANZURES-GARCÍA  

Benemérita Universidad Autónoma de Puebla (Facultad de Ciencias de la Computación), México Mexico
https://orcid.org/0000-0001-6138-3226

Authors

Miguel CAMACHO-HERNANDEZ  

Benemérita Universidad Autónoma de Puebla (Facultad de Ciencias de la Computación), México,  Mexico
https://orcid.org/0009-0002-8627-9876

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