eprintid: 10594
rev_number: 5
eprint_status: archive
userid: 2
dir: disk0/00/01/05/94
datestamp: 2024-01-24 23:30:23
lastmod: 2024-01-24 23:30:23
status_changed: 2024-01-24 23:30:23
type: article
metadata_visibility: show
creators_name: Hernandez, Leonel
creators_name: Uc Ríos, Carlos Eduardo
creators_name: Pranolo, Andri
creators_id: 
creators_id: carlos.uc@unini.edu.mx
creators_id: 
title: Design a Model-Based on Nonlinear Multiple Regression to Predict the Level of User Satisfaction when Optimizing a Traditional WLAN Using SDWN
ispublished: pub
subjects: uneat_eng
divisions: uninimx_produccion_cientifica
full_text_status: none
keywords: Software-Defined Wireless Networks (SDWN); optimization; predictive model; wireless networks; PPDIOO
abstract: Higher education institutions' wireless networks have different roles and network requirements, ranging from educational platforms and informative consultations. Currently, the inefficient use of network resources, poor wireless planning, and other factors, affect having a robust and stable network platform. Different authors have investigated the various strategies for the optimization of wireless infrastructures. Still, most of the cases studied aim to improve traditional performance variables without considering maximizing the level of user satisfaction, which represents a flaw that this research paper hopes to solve through SDWN and a predictive model.  The authors will determine an appropriate methodology to estimate the user's level of satisfaction through an algorithm or predictive model based on nonlinear multiple regression supported on network performance variables, making a characterization of the project's environment analyzing the wireless conditions. The investigation phases will follow the life cycle guidelines defined by the Cisco PPDIOO methodology (Prepare, Plan, Design, Implement, Operate, Optimize). As a result, it is expected that the project will be the beginning of academic research that will help create strategies to optimize the WiFi network of any educational institution to maximize user satisfaction. In short, the optimization process provides the network with differentiating factors through a modular design with variable modification of parameters according to the users' requirements and needs.
date: 2021-08
publication: International Journal on Advanced Science, Engineering and Information Technology
volume: 11
number: 4
pagerange: 1487
id_number: doi:10.18517/ijaseit.11.4.14463
refereed: TRUE
issn: 2088-5334
official_url: http://doi.org/10.18517/ijaseit.11.4.14463
access: open
language: en
citation:   Artículo Materias > Ingeniería <http://repositorio.unini.edu.mx/view/subjects/uneat=5Feng.html> Universidad Internacional Iberoamericana México > Investigación > Artículos y libros <http://repositorio.unini.edu.mx/view/divisions/uninimx=5Fproduccion=5Fcientifica.html> Abierto Inglés Higher education institutions' wireless networks have different roles and network requirements, ranging from educational platforms and informative consultations. Currently, the inefficient use of network resources, poor wireless planning, and other factors, affect having a robust and stable network platform. Different authors have investigated the various strategies for the optimization of wireless infrastructures. Still, most of the cases studied aim to improve traditional performance variables without considering maximizing the level of user satisfaction, which represents a flaw that this research paper hopes to solve through SDWN and a predictive model. The authors will determine an appropriate methodology to estimate the user's level of satisfaction through an algorithm or predictive model based on nonlinear multiple regression supported on network performance variables, making a characterization of the project's environment analyzing the wireless conditions. The investigation phases will follow the life cycle guidelines defined by the Cisco PPDIOO methodology (Prepare, Plan, Design, Implement, Operate, Optimize). As a result, it is expected that the project will be the beginning of academic research that will help create strategies to optimize the WiFi network of any educational institution to maximize user satisfaction. In short, the optimization process provides the network with differentiating factors through a modular design with variable modification of parameters according to the users' requirements and needs. metadata Hernandez, Leonel; Uc Ríos, Carlos Eduardo y Pranolo, Andri mail SIN ESPECIFICAR, carlos.uc@unini.edu.mx, SIN ESPECIFICAR       (2021) Design a Model-Based on Nonlinear Multiple Regression to Predict the Level of User Satisfaction when Optimizing a Traditional WLAN Using SDWN.  International Journal on Advanced Science, Engineering and Information Technology, 11 (4).  p. 1487.  ISSN 2088-5334