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Optimal controller selection and migration in large scale software defined networks for next generation internet of things

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posted on 2024-04-17, 08:23 authored by Mohammad Shahzad, Lu LiuLu Liu, Nacer Belkout, Nick Antonopoulos

The substantial amount of IoT traffic, coupled with control messages, places a heavy burden on SDN controllers, which compromises their capacity. We investigate how SDN can revolutionize the conventional approach, aiming to overcome the limitations of communication overhead. Additionally, we delve into the essential optimizations required to minimize control overhead and migrations. Determining the appropriate controller necessitates the implementation of a mechanism that justifies the selection. Once the optimal controller has been identified, migration can be initiated. This paper introduces a solution that employs the NSGA-II algorithm to achieve the optimal selection of controllers. We assess the performance of the NSGA-II migration approach linking with the length-based same destination aggregation proposed in our previous work, in terms of packet delivery, packet loss, performance metrics, and the cost associated with the selected optimal controller.

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Citation

Shahzad, M., Liu, L., Belkout, N. et al. Optimal controller selection and migration in large scale software defined networks for next generation internet of things. SN Appl. Sci. 5, 309 (2023)

Author affiliation

Comp' & Math' Sciences

Version

  • VoR (Version of Record)

Published in

SN Applied Sciences

Volume

5

Publisher

Springer Science and Business Media LLC

issn

2523-3963

eissn

2523-3971

Acceptance date

2023-10-17

Copyright date

2023

Available date

2024-04-17

Language

en

Deposited by

Professor Lu Liu

Deposit date

2024-04-15

Data Access Statement

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Rights Retention Statement

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