Deep reinforcement learning-based routing on software-defined networks
With an exponential increase in network traffic demands requiring quality of services, the
need for routing optimization has become more prominent. Recently, the advent of software …
need for routing optimization has become more prominent. Recently, the advent of software …
ResInNet: A novel deep neural network with feature reuse for Internet of Things
Deep neural networks (DNNs) have widely used in various Internet-of-Things (IoT)
applications. Pursuing superior performance is always a hot spot in the field of DNN …
applications. Pursuing superior performance is always a hot spot in the field of DNN …
Explaining deep learning-based traffic classification using a genetic algorithm
Traffic classification is widely used in various network functions such as software-defined
networking and network intrusion detection systems. Many traffic classification methods …
networking and network intrusion detection systems. Many traffic classification methods …
A semi-supervised stacked autoencoder approach for network traffic classification
Network traffic classification is an important task in modern communications. Several
approaches have been proposed to improve the performance of differentiating among …
approaches have been proposed to improve the performance of differentiating among …
Network traffic classifier with convolutional and recurrent neural networks for Internet of Things
A network traffic classifier (NTC) is an important part of current network monitoring systems,
being its task to infer the network service that is currently used by a communication flow (eg …
being its task to infer the network service that is currently used by a communication flow (eg …
Datanet: Deep learning based encrypted network traffic classification in sdn home gateway
A smart home network will support various smart devices and applications, eg, home
automation devices, E-health devices, regular computing devices, and so on. Most devices …
automation devices, E-health devices, regular computing devices, and so on. Most devices …
Efficient SDN-Based Traffic Monitoring in IoT Networks with Double Deep Q-Network
Abstract In an Internet of Things (IoT) environment, network traffic monitoring tasks are
intractable to achieve due to various IoT traffic types. Recently, the development of Software …
intractable to achieve due to various IoT traffic types. Recently, the development of Software …
An intelligent route computation approach based on real-time deep learning strategy for software defined communication systems
Software Defined Networking (SDN) is regarded as the next generation paradigm as it
simplifies the structure of the data plane and improves the resource utilization. However, in …
simplifies the structure of the data plane and improves the resource utilization. However, in …
A survey of machine learning techniques applied to software defined networking (SDN): Research issues and challenges
In recent years, with the rapid development of current Internet and mobile communication
technologies, the infrastructure, devices and resources in networking systems are becoming …
technologies, the infrastructure, devices and resources in networking systems are becoming …
A cost-sensitive deep learning-based approach for network traffic classification
Network traffic classification (NTC) plays an important role in cyber security and network
performance, for example in intrusion detection and facilitating a higher quality of service …
performance, for example in intrusion detection and facilitating a higher quality of service …