Title
Comprehensive Prediction Models of Control Traffic for SDN Controllers
Abstract
In SDN, as the control channel becomes a performance bottleneck, modeling the control channel traffic is important. Such a model is useful in predicting the control channel traffic for network provisioning. However, previously proposed models are quite limited in that they assume only the forwarding function of a specific controller for their models. To overcome the limitations, first, this paper analyzes the control traffic by seven functions (including forwarding function) of a controller. Then, we build a seven-function model to predict control channel usage and evaluate the prediction accuracy that achieves as high as 94%. Note that previous models did not have any quantitative evaluation. Our model is built with the Open Network Operating System (ONOS) controller and extended to Floodlight and POX controllers. We show that the extended model also achieves similar prediction accuracy (95%). Furthermore, we compare three controllers in terms of control channel usage through our model.
Year
DOI
Venue
2018
10.1109/NETSOFT.2018.8460111
2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft)
Keywords
Field
DocType
Control traffic,Control channel,OpenFlow,Software-defined networking,SDN controller,Scalability
Control channel,Bottleneck,Control theory,Computer science,Network operating system,Provisioning,OpenFlow,Software-defined networking,Distributed computing,Scalability
Conference
ISBN
Citations 
PageRank 
978-1-5386-4634-2
1
0.39
References 
Authors
4
3
Name
Order
Citations
PageRank
Bong-yeol Yu132.57
Gyeongsik Yang256.68
Chuck Yoo3299.49