Deep-Quality-EON Classifier

Elastic Optical Networks (EON) provide better spectrum allocation flexibility and scalability than traditional Wavelength Division Multiplexing networks and are suitable to support the increasing demand for Internet traffic. Those are circuit-switched networks that employ routing, modulation and spectrum allocation (RMSA) algorithms to establish optical circuits. To guarantee an efficient operation of these networks it is necessary to be able to monitor its behavior in a dynamic fashion in search of opportunities to improve its control. In this work, we propose Deep-Quality-EON, a deep learning-based model that classifies the efficiency of the resource allocation strategy applied in an EON solely based a snapshot of the spectrum allocation from the network. The deep learning classifier proposed was evaluated in several scenarios and the results obtained are promising, opening a new avenue on the research area of adaptive RMSA algorithms.