A Self-Optimizing Technique Based on Vertical Handover for Load Balancing in Heterogeneous Wireless Networks Using Big Data Analytics

With the heterogeneity and collaboration of many wireless operators (2G/3G/4G/5G/Wi-Fi), the priority is to effectively manage shared radio resources and ensure transparent user movement, which includes mechanisms such as mobility support, handover, quality of service (QoS), security and pricing. Th...

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Main Authors: Mykola Beshley, Natalia Kryvinska, Oleg Yaremko, Halyna Beshley
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/11/4737
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spelling doaj-9b47fd2038054625ae26089d9717ad2a2021-06-01T00:43:40ZengMDPI AGApplied Sciences2076-34172021-05-01114737473710.3390/app11114737A Self-Optimizing Technique Based on Vertical Handover for Load Balancing in Heterogeneous Wireless Networks Using Big Data AnalyticsMykola Beshley0Natalia Kryvinska1Oleg Yaremko2Halyna Beshley3Department of Telecommunications, Lviv Polytechnic National University, Bandera Str. 12, 79013 Lviv, UkraineDepartment of Information Systems, Faculty of Management, Comenius University, 25 82005 Bratislava, SlovakiaDepartment of Telecommunications, Lviv Polytechnic National University, Bandera Str. 12, 79013 Lviv, UkraineDepartment of Telecommunications, Lviv Polytechnic National University, Bandera Str. 12, 79013 Lviv, UkraineWith the heterogeneity and collaboration of many wireless operators (2G/3G/4G/5G/Wi-Fi), the priority is to effectively manage shared radio resources and ensure transparent user movement, which includes mechanisms such as mobility support, handover, quality of service (QoS), security and pricing. This requires considering the transition from the current mobile network architecture to a new paradigm based on collecting and storing information in big data for further analysis and decision making. For this reason, the management of big data analytics-driven networks in a cloud environment is an urgent issue, as the growth of its volume is becoming a challenge for today’s mobile infrastructure. Thus, we have formalized the problem of access network selection to improve the quality of mobile services through the efficient use of heterogeneous wireless network resources and optimal horizontal–vertical handover procedures. We proposed a method for adaptive selection of a wireless access node in a heterogeneous environment. A structural diagram of the optimization stages for wireless heterogeneous networks was developed, making it possible to improve the efficiency of their functioning. A model for studying the processes of functioning of a heterogeneous network environment is proposed. This model uses the methodology of big data evaluation to perform data transmission monitoring, analysis of tasks generated by network users, and statistical output of vertical handover initiation in (2G/3G/4G/5G/Wi-Fi) mobile communication infrastructure. The model allows studying the issues of optimization of operators’ networks by implementing the algorithm of redistribution of its network resources and providing flexible load balancing with QoS users in mind. The effectiveness of the proposed solutions is evaluated, and the performance of the heterogeneous network is increased by 16% when using the method of static reservation of network resources, compared to homogeneous networks, and another 13% when using a uniform distribution of resources and a dynamic process of their reservation, as well as compared to the previous method. An appropriate self-optimizing technique based on vertical handover for load balancing in heterogeneous wireless networks, using big data analytics, improves the QoS for users.https://www.mdpi.com/2076-3417/11/11/4737big data (BD)heterogeneous wireless networks (HWN)quality of service (QoS)self-optimizationload balancing (LB)vertical handover (VHO)
collection DOAJ
language English
format Article
sources DOAJ
author Mykola Beshley
Natalia Kryvinska
Oleg Yaremko
Halyna Beshley
spellingShingle Mykola Beshley
Natalia Kryvinska
Oleg Yaremko
Halyna Beshley
A Self-Optimizing Technique Based on Vertical Handover for Load Balancing in Heterogeneous Wireless Networks Using Big Data Analytics
Applied Sciences
big data (BD)
heterogeneous wireless networks (HWN)
quality of service (QoS)
self-optimization
load balancing (LB)
vertical handover (VHO)
author_facet Mykola Beshley
Natalia Kryvinska
Oleg Yaremko
Halyna Beshley
author_sort Mykola Beshley
title A Self-Optimizing Technique Based on Vertical Handover for Load Balancing in Heterogeneous Wireless Networks Using Big Data Analytics
title_short A Self-Optimizing Technique Based on Vertical Handover for Load Balancing in Heterogeneous Wireless Networks Using Big Data Analytics
title_full A Self-Optimizing Technique Based on Vertical Handover for Load Balancing in Heterogeneous Wireless Networks Using Big Data Analytics
title_fullStr A Self-Optimizing Technique Based on Vertical Handover for Load Balancing in Heterogeneous Wireless Networks Using Big Data Analytics
title_full_unstemmed A Self-Optimizing Technique Based on Vertical Handover for Load Balancing in Heterogeneous Wireless Networks Using Big Data Analytics
title_sort self-optimizing technique based on vertical handover for load balancing in heterogeneous wireless networks using big data analytics
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2021-05-01
description With the heterogeneity and collaboration of many wireless operators (2G/3G/4G/5G/Wi-Fi), the priority is to effectively manage shared radio resources and ensure transparent user movement, which includes mechanisms such as mobility support, handover, quality of service (QoS), security and pricing. This requires considering the transition from the current mobile network architecture to a new paradigm based on collecting and storing information in big data for further analysis and decision making. For this reason, the management of big data analytics-driven networks in a cloud environment is an urgent issue, as the growth of its volume is becoming a challenge for today’s mobile infrastructure. Thus, we have formalized the problem of access network selection to improve the quality of mobile services through the efficient use of heterogeneous wireless network resources and optimal horizontal–vertical handover procedures. We proposed a method for adaptive selection of a wireless access node in a heterogeneous environment. A structural diagram of the optimization stages for wireless heterogeneous networks was developed, making it possible to improve the efficiency of their functioning. A model for studying the processes of functioning of a heterogeneous network environment is proposed. This model uses the methodology of big data evaluation to perform data transmission monitoring, analysis of tasks generated by network users, and statistical output of vertical handover initiation in (2G/3G/4G/5G/Wi-Fi) mobile communication infrastructure. The model allows studying the issues of optimization of operators’ networks by implementing the algorithm of redistribution of its network resources and providing flexible load balancing with QoS users in mind. The effectiveness of the proposed solutions is evaluated, and the performance of the heterogeneous network is increased by 16% when using the method of static reservation of network resources, compared to homogeneous networks, and another 13% when using a uniform distribution of resources and a dynamic process of their reservation, as well as compared to the previous method. An appropriate self-optimizing technique based on vertical handover for load balancing in heterogeneous wireless networks, using big data analytics, improves the QoS for users.
topic big data (BD)
heterogeneous wireless networks (HWN)
quality of service (QoS)
self-optimization
load balancing (LB)
vertical handover (VHO)
url https://www.mdpi.com/2076-3417/11/11/4737
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