An overview on application of machine learning techniques in optical networks
Today's telecommunication networks have become sources of enormous amounts of widely
heterogeneous data. This information can be retrieved from network traffic traces, network …
heterogeneous data. This information can be retrieved from network traffic traces, network …
A survey on machine learning techniques for routing optimization in SDN
In conventional networks, there was a tight bond between the control plane and the data
plane. The introduction of Software-Defined Networking (SDN) separated these planes, and …
plane. The introduction of Software-Defined Networking (SDN) separated these planes, and …
Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case
Abstract Deep Reinforcement Learning (DRL) has shown a dramatic improvement in
decision-making and automated control problems. Consequently, DRL represents a …
decision-making and automated control problems. Consequently, DRL represents a …
A survey of networking applications applying the software defined networking concept based on machine learning
The main task of future networks is to build, as much as possible, intelligent networking
architectures for intellectualization, activation, and customization. Software-defined …
architectures for intellectualization, activation, and customization. Software-defined …
Machine learning meets communication networks: Current trends and future challenges
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …
massively expanding number of connected devices and online services, require intelligent …
Survey on machine learning for traffic-driven service provisioning in optical networks
T Panayiotou, M Michalopoulou… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The unprecedented growth of the global Internet traffic, coupled with the large spatio-
temporal fluctuations that create, to some extent, predictable tidal traffic conditions, are …
temporal fluctuations that create, to some extent, predictable tidal traffic conditions, are …
Artificial intelligence enabled software‐defined networking: a comprehensive overview
M Latah, L Toker - IET networks, 2019 - Wiley Online Library
Software‐defined networking (SDN) represents a promising networking architecture that
combines central management and network programmability. SDN separates the control …
combines central management and network programmability. SDN separates the control …
A reinforcement learning-based network traffic prediction mechanism in intelligent internet of things
Intelligent Internet of Things (IIoT) is comprised of various wireless and wired networks for
industrial applications, which makes it complex and heterogeneous. The openness of IIoT …
industrial applications, which makes it complex and heterogeneous. The openness of IIoT …
Machine learning for optical fiber communication systems: An introduction and overview
Optical networks generate a vast amount of diagnostic, control, and performance monitoring
data. When information is extracted from these data, reconfigurable network elements and …
data. When information is extracted from these data, reconfigurable network elements and …
Applications of machine learning in networking: a survey of current issues and future challenges
Communication networks are expanding rapidly and becoming increasingly complex. As a
consequence, the conventional rule-based algorithms or protocols may no longer perform at …
consequence, the conventional rule-based algorithms or protocols may no longer perform at …