A cost‐effective and load‐balanced controller placement method in software‐defined networks
Summary A network incorporates nodes, and each node can communicate with each other through some links. An efficient way to maintain the communication between nodes is to divide a network into several subnetworks, called clusters. We have developed a new clustering algorithm and applied our method f...
Gespeichert in:
Veröffentlicht in: | International journal of network management 2022-09, Vol.32 (5), p.n/a |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Summary
A network incorporates nodes, and each node can communicate with each other through some links. An efficient way to maintain the communication between nodes is to divide a network into several subnetworks, called clusters. We have developed a new clustering algorithm and applied our method for the controller placement in software‐defined networks (SDNs). Placing a controller in its appropriate location by balancing the loads and optimizing the latency even in case of a failure scenario becomes a challenging task. Thus, we have proposed a multi‐controller placement algorithm that can minimize the average (Sw‐Co) latency in such a way that the network switches are fairly distributed over clusters. This distribution helps to balance loads of switches among controllers even in the case of a controller failure scenario. We have also simulated three other existing algorithms for comparison. Experiment results show that our algorithm is a cost‐effective solution as compared with other existing algorithms. We have also shown that our proposed method balanced loads of switches between controllers in a SDN network and generates lower average (Sw‐Co) latency with and without a controller failure.
We have proposed a mathematical algorithm to minimize the average‐case switch to controller latency by balancing loads of switches among controllers and also minimize the network cost in SDN. We have also analyzed our method for one controller failure scenario to present the effect of a load‐balanced system. A statistical analysis has proved that our proposed method gives a consistent solution than other existing methods. |
---|---|
ISSN: | 1055-7148 1099-1190 |
DOI: | 10.1002/nem.2199 |