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    Failure mitigation in software defined networking employing load type prediction

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    ICC_SDN_Mitigation.pdf
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    Description:
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    Type
    Conference Paper
    Authors
    Bouacida, Nader cc
    AlGhadhban, Amer M. cc
    Alalmaei, Shiyam Mohammed Abdullah
    Mohammed, Haneen cc
    Shihada, Basem cc
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2017-07-31
    Online Publication Date
    2017-07-31
    Print Publication Date
    2017-05
    Permanent link to this record
    http://hdl.handle.net/10754/625712
    
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    Abstract
    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.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2017 IEEE International Conference on Communications (ICC)
    Conference/Event name
    2017 IEEE International Conference on Communications, ICC 2017
    DOI
    10.1109/ICC.2017.7997295
    Additional Links
    http://ieeexplore.ieee.org/document/7997295/
    ae974a485f413a2113503eed53cd6c53
    10.1109/ICC.2017.7997295
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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