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Unsupervised and Supervised Activity Analysis of Drone Sensor Data Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Simulation of Fuzzy Inference System to Task Scheduling in Queueing Networks

Authors : Eduyn Ramiro López-Santana, Carlos Franco-Franco, Juan Carlos Figueroa-García

Published in: Applied Computer Sciences in Engineering

Publisher: Springer International Publishing

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Abstract

This paper presents a simulation approach of the problem of scheduling customers in a queuing networks using a fuzzy inference system. Usually, in the queuing systems there are rules as round robin, equiprobable, shortest queue, among others, to schedule customers, however the condition of the system like the cycle time, utilization and the length of queue is difficult to measure. We propose a fuzzy inference system in order to determine the status in the system using input variables like the length queue and utilization. Our simulation shows an improvement in the performance measures compared with traditional scheduling policies.

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previous chapter A Hybrid System Dynamics and Fuzzy Logic Approach to Social Problem of Corruption in Colombia
next chapter Estimation of Quantile Confidence Intervals for Queueing Systems Based on the Bootstrap Methodology
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Metadata
Title
Simulation of Fuzzy Inference System to Task Scheduling in Queueing Networks
Authors
Eduyn Ramiro López-Santana
Carlos Franco-Franco
Juan Carlos Figueroa-García
Copyright Year
2017
Book
Applied Computer Sciences in Engineering

Print ISBN: 978-3-319-66962-5

Electronic ISBN: 978-3-319-66963-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-66963-2_24

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