Application of Real-time fan scheduling in exploration-exploitation to optimize minimum function objectives

• Autorzy: Larios-Gómez Mariano , Quintero-Flores Perfecto M. , Anzures-García Mario , Camacho-Hernandez Miguel

Identyfikatory

DOI

10.35784/acs-2023-13

• Języki publikacji: EN

Abstrakty

EN

This paper presents the application of a task scheduling algorithm called Fan based on artificial intelligence technique such as genetic algorithms for the problem of finding minima in objective functions, where equations are predefined to measure the return on investment. This work combines the methodologies of population exploration and exploitation. Results with good aptitudes are obtained until a better learning based on non-termination conditions is found, until the individual provides a better predisposi¬tion, adhering to the established constraints, exhausting all possible options and satisfying the stopping 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 a few iterations. In the second stage, exploitation was improved, giving the algorithm a better performance in convergence and feasibility. As a result, a population was used and iterations were applied with a fan algorithm and better predisposition was obtained, which occurs in asynchronous processes while scheduling in real time.

Słowa kluczowe

EN

real-time task scheduling; genetic algorithms; concurrent computing

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2023
• Tom: Vol. 19, no 2
• Strony: 43--54
• Opis fizyczny: Bibliogr. 19 poz., fig.

Twórcy

autor

Larios-Gómez Mariano

• Universidad Autónoma de Tlaxcala (Facultad de Ciencias Básicas, Ingeniería y Tecnología), México
• Benemérita Universidad Autónoma de Puebla (Facultad de Ciencias de la Computación), México

• https://orcid.org/000-0002-2089-0608

autor

Quintero-Flores Perfecto M.

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

• https://orcid.org/0000-0001-7651-4364

autor

Anzures-García Mario

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

• https://orcid.org/0000-0001-6138-322

autor

Camacho-Hernandez Miguel

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

• https://orcid.org/0009-0002-8627-9876

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