Performance Comparison of Various Controllers in Different SDN Topologies

B. Keerthana, Mamatha Balachandra, Harishchandra Hebbar, Balachandra Muniyal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


The continuous surge in the number of devices connected to the Internet and the added lineup of Internet of things (IoT) devices to these networks have led to the complexity of connected devices. One of the ways to overcome this issue is by the introduction of software-defined network (SDN), and the management of these networks is done by the use of various controllers. Addition of a controller improves the management of flow control and also adds intelligence to a network. The performance of three such popular controllers; the Ovs, PoX, and Ryu are used in this study. This work is carried out in an SDN environment with varying topologies and packet transmission. Network performance is considered as an important factor in communication. The main aim of the study is to check any change in the round-trip time with respect to the controller and find whether there is any relationship between the number of nodes in the network and round-trip time. This work is designed based on the utilization of mininet in various network topologies. The other aim of the study was to interpret the change in the round-trip time with respect to the varying topologies. The correlation between the performance of the network and the controller type is also analyzed in this study.

Original languageEnglish
Title of host publicationExpert Clouds and Applications - Proceedings of ICOECA 2021
EditorsI. Jeena Jacob, Francisco M. Gonzalez-Longatt, Selvanayaki Kolandapalayam Shanmugam, Ivan Izonin
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages13
ISBN (Print)9789811621253
Publication statusPublished - 2022
EventInternational Conference on Expert Clouds and Applications, ICOECA 2021 - Bangalore
Duration: 18-02-202119-02-2021

Publication series

NameLecture Notes in Networks and Systems
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


ConferenceInternational Conference on Expert Clouds and Applications, ICOECA 2021

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications


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