Failure mitigation in software defined networking employing load type prediction
Type
Conference PaperAuthors
Bouacida, Nader
AlGhadhban, Amer M.

Alalmaei, Shiyam Mohammed Abdullah
Mohammed, Haneen

Shihada, Basem

KAUST Department
Computer Science ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Date
2017-07-31Online Publication Date
2017-07-31Print Publication Date
2017-05Permanent link to this record
http://hdl.handle.net/10754/625712
Metadata
Show full item recordAbstract
The controller is a critical piece of the SDN architecture, where it is considered as the mastermind of SDN networks. Thus, its failure will cause a significant portion of the network to fail. Overload is one of the common causes of failure since the controller is frequently invoked by new flows. Even through SDN controllers are often replicated, the significant recovery time can be an overkill for the availability of the entire network. In order to overcome the problem of the overloaded controller failure in SDN, this paper proposes a novel controller offload solution for failure mitigation based on a prediction module that anticipates the presence of a harmful long-term load. In fact, the long-standing load would eventually overwhelm the controller leading to a possible failure. To predict whether the load in the controller is short-term or long-term load, we used three different classification algorithms: Support Vector Machine, k-Nearest Neighbors, and Naive Bayes. Our evaluation results demonstrate that Support Vector Machine algorithm is applicable for detecting the type of load with an accuracy of 97.93% in a real-time scenario. Besides, our scheme succeeded to offload the controller by switching between the reactive and proactive mode in response to the prediction module output.Citation
Bouacida N, Alghadhban A, Alalmaei S, Mohammed H, Shihada B (2017) Failure mitigation in software defined networking employing load type prediction. 2017 IEEE International Conference on Communications (ICC). Available: http://dx.doi.org/10.1109/ICC.2017.7997295.Conference/Event name
2017 IEEE International Conference on Communications, ICC 2017Additional Links
http://ieeexplore.ieee.org/document/7997295/ae974a485f413a2113503eed53cd6c53
10.1109/ICC.2017.7997295