Comparative analysis of load balancing methods based on SDN/NFV

The purpose of the study was to determine the advantages and disadvantages of using load balancing methods in networks based on Software-Defined Networking and Network Functions Virtualisation technologies. Particular attention was paid to comparing the effectiveness of different approaches to balancing, including centralised and distributed methods, and the use of intelligent algorithms for load forecasting. The analysis helped to identify the advantages and disadvantages of each method, and their ability to adapt to changing network traffic conditions, considering such parameters as bandwidth, latency, packet loss, and energy efficiency. The paper discussed methods of load balancing in networks based on Software-Defined Networking and Network Functions Virtualisation technologies, which are important for ensuring the efficiency, scalability, and adaptability of modern networks. The key challenges faced by these technologies are described, such as the dynamism and unpredictability of traffic, resource optimisation, energy efficiency, and the integration of intelligent algorithms for load forecasting and energy consumption reduction. The study presents a comparison of various load balancing methods, including centralised and distributed traffic management, and the use of virtual balancers and adaptive traffic redirection algorithms. Particular attention was paid to analysing the impact of these methods on throughput, latency, packet loss, and energy efficiency under different traffic conditions. The role of machine learning in optimising load balancing processes, and the possibilities of integrating Software-Defined Networking and Network Functions Virtualisation into hybrid networks were considered. According to the results of the study, the use of balancing methods based on Software-Defined Networking/Network Functions Virtualisation can significantly improve network efficiency, reduce latency and increase throughput, while reducing energy consumption under high loads. Key results for Ukraine, where the integration of Software-Defined Networking/Network Functions Virtualisation into the telecommunications infrastructure can become the basis for improving the quality of services, optimising costs, and ensuring a high level of security in the context of digital transformation and infrastructure modernisation, are derived

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Publication Details

Journal
Information Technology and Computer Engineering
Published
2025-03-04
DOI
https://doi.org/10.63341/vitce/1.2025.124
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
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article

Comparative analysis of load balancing methods based on SDN/NFV

Oleksandr Berestovenko
Information Technology and Computer Engineering
Software-Defined Networks and 5G
article

Comparative analysis of load balancing methods based on SDN/NFV

Oleksandr Berestovenko
article en

Abstract

The purpose of the study was to determine the advantages and disadvantages of using load balancing methods in networks based on Software-Defined Networking and Network Functions Virtualisation technologies. Particular attention was paid to comparing the effectiveness of different approaches to balancing, including centralised and distributed methods, and the use of intelligent algorithms for load forecasting. The analysis helped to identify the advantages and disadvantages of each method, and their ability to adapt to changing network traffic conditions, considering such parameters as bandwidth, latency, packet loss, and energy efficiency. The paper discussed methods of load balancing in networks based on Software-Defined Networking and Network Functions Virtualisation technologies, which are important for ensuring the efficiency, scalability, and adaptability of modern networks. The key challenges faced by these technologies are described, such as the dynamism and unpredictability of traffic, resource optimisation, energy efficiency, and the integration of intelligent algorithms for load forecasting and energy consumption reduction. The study presents a comparison of various load balancing methods, including centralised and distributed traffic management, and the use of virtual balancers and adaptive traffic redirection algorithms. Particular attention was paid to analysing the impact of these methods on throughput, latency, packet loss, and energy efficiency under different traffic conditions. The role of machine learning in optimising load balancing processes, and the possibilities of integrating Software-Defined Networking and Network Functions Virtualisation into hybrid networks were considered. According to the results of the study, the use of balancing methods based on Software-Defined Networking/Network Functions Virtualisation can significantly improve network efficiency, reduce latency and increase throughput, while reducing energy consumption under high loads. Key results for Ukraine, where the integration of Software-Defined Networking/Network Functions Virtualisation into the telecommunications infrastructure can become the basis for improving the quality of services, optimising costs, and ensuring a high level of security in the context of digital transformation and infrastructure modernisation, are derived

Information Technology and Computer EngineeringVol. 22(1)
National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” (UA)
Affordable and clean energy
Openalex Percentile: Top 87%
Software-Defined Networks and 5G
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