UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 8
August-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2308550


Registration ID:
523790

Page Number

f422-f427

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Title

Modeling SDN using Graph Neural Networks

Abstract

Building self-driving Software-Defined Networks requires network modeling, particularly to identify the best routing protocols that satisfy the objectives stated by administrators. However, the requirements for providing precise estimates of pertinent performance indicators like latency and jitter are not addressed by present modeling methodologies. In this study, we provide a unique Graph Neural Network (GNN) model capable of comprehending the intricate link between topology, routing, and input traffic to generate precise estimates of the mean delay and jitter for each source/destination pair. Because GNN is designed to learn and model data that is organized as graphs, our model can generalize over any topologies, routing protocols, and varying traffic intensity. Additionally, we demonstrate the model's potential for network operation through the presentation of a number of use cases that demonstrate its successful application in the optimisation of delay and jitter for each source-destination pair as well as its generalization abilities by reasoning in topologies and routing schemes that were not encountered during training.

Key Words

Software Designed Network,Graph Neural Network,Neural Network

Cite This Article

"Modeling SDN using Graph Neural Networks ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.f422-f427, August-2023, Available :http://www.jetir.org/papers/JETIR2308550.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Modeling SDN using Graph Neural Networks ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppf422-f427, August-2023, Available at : http://www.jetir.org/papers/JETIR2308550.pdf

Publication Details

Published Paper ID: JETIR2308550
Registration ID: 523790
Published In: Volume 10 | Issue 8 | Year August-2023
DOI (Digital Object Identifier):
Page No: f422-f427
Country: Rohtak, Haryana, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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