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

Abstract 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, w...

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Bibliographic Details
Main Authors: Mohammad Shahzad, Lu Liu, Nacer Belkout, Nick Antonopoulos
Format: Article
Language:English
Published: Springer 2023-11-01
Series:SN Applied Sciences
Subjects:
Online Access:https://doi.org/10.1007/s42452-023-05535-0
Description
Summary:Abstract 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.
ISSN:2523-3963
2523-3971