Enhancing Network Management Through Machine Learning in Software-Defined Networking

Enhancing Network Management Through Machine Learning in Software-Defined Networking

Registration ID: IJNRD_220172

Published ID: IJNRD2404880

DOI: Click Here to Get

Hemant Kumar Bhardwaj , Arvind Panwar

SDN (Software-Defined Networking,) Machine Learning Integration, Traffic Classification, Evolution Network Management, Optimization Intelligent

The increasing diversification of Internet applications and the ongoing evolution of network infrastructure, fueled by emerging technologies, have introduced complexities to network management. Effectively classifying network traffic is crucial for managing network resources based on quality of service and security requirements. However, conventional traffic classification methods relying on Deep Packet Inspection fall short of meeting the demanding scalability, security, and privacy criteria. The centralized controller in Software-Defined Networking offers a comprehensive network view, easing traffic analysis and providing direct programming capabilities. This allows for dynamic adjustments of traffic flows to meet evolving network requirements. The integration of Machine Learning techniques, along with these features, enables the infusion of intelligence into networks, optimizing their performance and enhancing management and maintenance. In this context, our work aims to conduct a Systematic Literature Review on traffic classification in Software-Defined Networking using Machine Learning techniques. Additionally, we systematically analyze and organize the chosen seminal works based on the categorization of traffic classes and the employed Machine Learning techniques, drawing meaningful research conclusions. Finally, we identify new challenges and propose future research directions in this domain.

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"Enhancing Network Management Through Machine Learning in Software-Defined Networking", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 4, page no.i703-i720, April-2024, Available :https://ijnrd.org/papers/IJNRD2404880.pdf

Volume 9 Issue 4, April-2024

Pages : i703-i720

Paper Reg. ID: IJNRD_220172

Published Paper Id: IJNRD2404880

Downloads: 000121139

Research Area: Computer Science & Technology 

Country: GHAZIABAD, Uttar Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404880.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404880

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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