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

Shahzad, Mohammad; Liu, Lu; Belkout, Nacer; Antonopoulos, Nick

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.

Citation

Shahzad, M., Liu, L., Belkout, N., & Antonopoulos, N. (2023). Optimal controller selection and migration in large scale software defined networks for next generation internet of things. SN Applied Sciences, 5(12), Article 309. https://doi.org/10.1007/s42452-023-05535-0

• Journal Article Type: Article
• Acceptance Date: Oct 17, 2023
• Online Publication Date: Nov 4, 2023
• Publication Date: 2023
• Deposit Date: Jan 8, 2024
• Publicly Available Date: Jan 8, 2024
• Journal: SN Applied Sciences
• Electronic ISSN: 3004-9261
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 5
• Issue: 12
• Article Number: 309
• DOI: https://doi.org/10.1007/s42452-023-05535-0
• Keywords: Internet of things, Optimal controller selection, Software defined networking (SDN), SDN migration
• Public URL: http://researchrepository.napier.ac.uk/Output/3373991