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# Knowledge-Defined Networking

###### [Arxiv] (https://arxiv.org/abs/1606.06222):
###### [ACM SIGCOMM-CCR] (https://dl.acm.org/citation.cfm?id=3138810):
Albert Mestres,	Alberto Rodriguez-Natal, Josep Carner, Pere Barlet-Ros, Eduard Alarcón, Marc Solé, Victor Muntés-Mulero, David Meyer, Sharon Barkai, Mike J. Hibbett, Giovani Estrada, Khaldun Ma'ruf, Florin Coras, Vina Ermagan, Hugo Latapie, Chris Cassar, John Evans, Fabio Maino, Jean Walrand and Albert Cabellos

The research community has considered in the past the application of Artificial Intelligence (AI) techniques to control and operate networks. A notable example is the Knowledge Plane proposed by D.Clark et al. However, such techniques have not been extensively prototyped or deployed in the field yet. In this paper, we explore the reasons for the lack of adoption and posit that the rise of two recent paradigms: Software-Defined Networking (SDN) and Network Analytics (NA), will facilitate the adoption of AI techniques in the context of network operation and control. We describe a new paradigm that accommodates and exploits SDN, NA and AI, and provide use cases that illustrate its applicability and benefits. We also present simple experimental results that support its feasibility. We refer to this new paradigm as Knowledge-Defined Networking (KDN).

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Code and datasets [here](https://github.com/knowledgedefinednetworking/-knowledge-defined-networking).

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# Knowledge-Defined Networking Preliminary Experiment

## Overlay-Underlay Network modeling

Datasets available here [here](http://knowledgedefinednetworking.org/).

## VNF modeling

Datasets available here [here](http://knowledgedefinednetworking.org/).

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author: amestres@ac.upc.edu

* [MATLAB](https://www.mathworks.com/products/matlab.html)
* [PYLEARN2](http://deeplearning.net/software/pylearn2/)
* [KDN](https://arxiv.org/abs/1606.06222)
* [OMNeT++](https://omnetpp.org/)

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