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Design a Model-Based on Nonlinear Multiple Regression to Predict the Level of User Satisfaction when Optimizing a Traditional WLAN Using SDWN

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@article{IJASEIT14463,
   author = {Leonel Hernandez and Carlos Eduardo Uc Rios and Andri Pranolo},
   title = {Design a Model-Based on Nonlinear Multiple Regression to Predict the Level of User Satisfaction when Optimizing a Traditional WLAN Using SDWN},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {11},
   number = {4},
   year = {2021},
   pages = {1487--1493},
   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.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14463},
   doi = {10.18517/ijaseit.11.4.14463}
}

EndNote

%A Hernandez, Leonel
%A Uc Rios, Carlos Eduardo
%A Pranolo, Andri
%D 2021
%T Design a Model-Based on Nonlinear Multiple Regression to Predict the Level of User Satisfaction when Optimizing a Traditional WLAN Using SDWN
%B 2021
%9 Software-Defined Wireless Networks (SDWN); optimization; predictive model; wireless networks; PPDIOO.
%! Design a Model-Based on Nonlinear Multiple Regression to Predict the Level of User Satisfaction when Optimizing a Traditional WLAN Using SDWN
%K Software-Defined Wireless Networks (SDWN); optimization; predictive model; wireless networks; PPDIOO.
%X 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.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14463
%R doi:10.18517/ijaseit.11.4.14463
%J International Journal on Advanced Science, Engineering and Information Technology
%V 11
%N 4
%@ 2088-5334

IEEE

Leonel Hernandez,Carlos Eduardo Uc Rios and Andri Pranolo,"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, vol. 11, no. 4, pp. 1487-1493, 2021. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.11.4.14463.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Hernandez, Leonel
AU  - Uc Rios, Carlos Eduardo
AU  - Pranolo, Andri
PY  - 2021
TI  - Design a Model-Based on Nonlinear Multiple Regression to Predict the Level of User Satisfaction when Optimizing a Traditional WLAN Using SDWN
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 11 (2021) No. 4
Y2  - 2021
SP  - 1487
EP  - 1493
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - Software-Defined Wireless Networks (SDWN); optimization; predictive model; wireless networks; PPDIOO.
N2  - 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.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14463
DO  - 10.18517/ijaseit.11.4.14463

RefWorks

RT Journal Article
ID 14463
A1 Hernandez, Leonel
A1 Uc Rios, Carlos Eduardo
A1 Pranolo, Andri
T1 Design a Model-Based on Nonlinear Multiple Regression to Predict the Level of User Satisfaction when Optimizing a Traditional WLAN Using SDWN
JF International Journal on Advanced Science, Engineering and Information Technology
VO 11
IS 4
YR 2021
SP 1487
OP 1493
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 Software-Defined Wireless Networks (SDWN); optimization; predictive model; wireless networks; PPDIOO.
AB 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.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14463
DO  - 10.18517/ijaseit.11.4.14463