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

被引:1
|
作者
Shahzad, Mohammad [1 ]
Liu, Lu [1 ]
Belkout, Nacer [2 ]
Antonopoulos, Nick [3 ]
机构
[1] Univ Leicester, Sch Comp & Math Sci, Leicester, England
[2] Univ Sci & Technol, Dept Comp Sci, Algiers, Algeria
[3] Edinburgh Napier Univ, Edinburgh, Scotland
来源
SN APPLIED SCIENCES | 2023年 / 5卷 / 12期
关键词
Internet of things; Optimal controller selection; Software defined networking (SDN); SDN migration;
D O I
10.1007/s42452-023-05535-0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. The article selects optimal controller based on performance and cost calculated mathematically reducing control overhead.NSGA-II is employed to select controller to reduce migrations and control communication.NSGA-II is linked with our previous work burst assembly and compared with 4 state-of-the-art methods.
引用
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页数:10
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