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2021 | OriginalPaper | Chapter

Comparative Analysis of Traffic and Congestion in Software-Defined Networks

Authors : Anil Singh Parihar, Kunal Sinha, Paramvir Singh, Sameer Cherwoo

Published in: Computer Networks, Big Data and IoT

Publisher: Springer Singapore

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Abstract

The different methods used for classifying traffic along with the prediction of congestion and performance in software-defined networks were discussed. Although congestion prediction has foreseen many challenges, the algorithms did not give very accurate results. But over a period of time, several methods have been discovered to identify and predict the performance and congestion in software-defined networks (SDN). In this article, various techniques of classification were compared and predicted through tables and graphs.

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previous chapter In-network Data Aggregation Techniques for Wireless Sensor Networks: A Survey
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Metadata
Title
Comparative Analysis of Traffic and Congestion in Software-Defined Networks
Authors
Anil Singh Parihar
Kunal Sinha
Paramvir Singh
Sameer Cherwoo
Copyright Year
2021
Publisher
Springer Singapore
Book
Computer Networks, Big Data and IoT

Print ISBN: 978-981-16-0964-0

Electronic ISBN: 978-981-16-0965-7

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-16-0965-7_69