A Fuzzy Inference System to Scheduling Tasks in Queueing Systems

Carlos Alberto Franco Franco, eduyn ramiro Lopéz-Santana, Juan Carlos Figueroa-Garcia

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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.
Original languageEnglish (US)
Pages (from-to)286-297
Number of pages12
JournalLecture Notes in Computer Science
Volume10363
StatePublished - Jul 21 2017

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Queuing System
Fuzzy Inference System
Task Scheduling
Fuzzy inference
Queueing System
Queue
Customers
Scheduling
Scheduling Policy
Queue Length
Performance Measures
Experiment
Experiments

Cite this

Franco Franco, C. A., Lopéz-Santana, E. R., & Figueroa-Garcia, J. C. (2017). A Fuzzy Inference System to Scheduling Tasks in Queueing Systems. Lecture Notes in Computer Science, 10363, 286-297.
Franco Franco, Carlos Alberto ; Lopéz-Santana, eduyn ramiro ; Figueroa-Garcia, Juan Carlos . / A Fuzzy Inference System to Scheduling Tasks in Queueing Systems. In: Lecture Notes in Computer Science. 2017 ; Vol. 10363. pp. 286-297.
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Franco Franco, CA, Lopéz-Santana, ER & Figueroa-Garcia, JC 2017, 'A Fuzzy Inference System to Scheduling Tasks in Queueing Systems', Lecture Notes in Computer Science, vol. 10363, pp. 286-297.

A Fuzzy Inference System to Scheduling Tasks in Queueing Systems. / Franco Franco, Carlos Alberto; Lopéz-Santana, eduyn ramiro; Figueroa-Garcia, Juan Carlos .

In: Lecture Notes in Computer Science, Vol. 10363, 21.07.2017, p. 286-297.

Research output: Contribution to journalArticle

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AB - 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.

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