A fuzzy inference system to scheduling tasks in queueing systems

Eduyn Ramiro López-Santana, Carlos Franco, Juan Carlos Figueroa-Garcia

Producción científica: Capítulo en Libro/ReporteContribución a la conferencia

2 Citas (Scopus)

Resumen

This paper studies the problem of scheduling customers or tasks in a queuing system. Generally the customers or a set of tasks in queuing system are attended according with different rules as round robin, equiprobable, shortest queue, among others. However, the condition of the system like the work in process, utilization and the length of queue is difficult to measure. We propose to use a fuzzy inference system in order to determine the status in the system depended of input variables like the length queue and the utilization. The experiment results shows an improvement in the performance measures compared with traditional scheduling policies.

Idioma originalInglés estadounidense
Título de la publicación alojadaIntelligent Computing Methodologies - 13th International Conference, ICIC 2017, Proceedings
EditoresAbir Hussain, Kyungsook Han, De-Shuang Huang, M. Michael Gromiha
EditorialSpringer
Páginas286-297
Número de páginas12
ISBN (versión impresa)9783319633145
DOI
EstadoPublicada - 2017
Evento13th International Conference on Intelligent Computing, ICIC 2017 - Liverpool, Reino Unido
Duración: ago. 7 2017ago. 10 2017

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen10363 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia13th International Conference on Intelligent Computing, ICIC 2017
País/TerritorioReino Unido
CiudadLiverpool
Período8/7/178/10/17

Áreas temáticas de ASJC Scopus

  • Ciencia computacional teórica
  • Ciencia de la Computación General

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