most citedA Long Short-Term Memory Recurrent Neural Network Framework for Network Traffic Matrix Prediction

161 citations · 192 across the 3 of their papers we have counts for

collaborators

5 papers

cs.NI2017

NeuTM: A Neural Network-based Framework for Traffic Matrix Prediction in SDN

Abdelhadi Azzouni, Guy Pujolle

This paper presents NeuTM, a framework for network Traffic Matrix (TM) prediction based on Long Short-Term Memory Recurrent Neural Networks (LSTM RNNs). TM prediction is defined as…

cs.NI2017

NeuRoute: Predictive Dynamic Routing for Software-Defined Networks

Abdelhadi Azzouni, Raouf Boutaba, Guy Pujolle

This paper introduces NeuRoute, a dynamic routing framework for Software Defined Networks (SDN) entirely based on machine learning, specifically, Neural Networks. Current SDN/OpenF…

cs.NI2017161 cited

A Long Short-Term Memory Recurrent Neural Network Framework for Network Traffic Matrix Prediction

Abdelhadi Azzouni, Guy Pujolle

Network Traffic Matrix (TM) prediction is defined as the problem of estimating future network traffic from the previous and achieved network traffic data. It is widely used in netw…

cs.NI201731 cited

sOFTDP: Secure and Efficient Topology Discovery Protocol for SDN

Abdelhadi Azzouni, Raouf Boutaba, Nguyen Thi Mai Trang +1

Topology discovery is one of the most critical tasks of Software-Defined Network (SDN) controllers. Current SDN controllers use the OpenFlow Discovery Protocol (OFDP) as the de-fac…

cs.NI2017

Limitations of OpenFlow Topology Discovery Protocol

Abdelhadi Azzouni, Nguyen Thi Mai Trang, Raouf Boutaba +1

OpenFlow Discovery Protocol (OFDP) is the de-facto protocol used by OpenFlow controllers to discover the underlying topology. In this paper, we show that OFDP has some serious secu…