On removing routing protocol from future wireless networks: A real-time deep learning approach for intelligent traffic control
Recently, deep learning has appeared as a breakthrough machine learning technique for
various areas in computer science as well as other disciplines. However, the application of …
various areas in computer science as well as other disciplines. However, the application of …
State-of-the-art deep learning: Evolving machine intelligence toward tomorrow's intelligent network traffic control systems
Currently, the network traffic control systems are mainly composed of the Internet core and
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …
The deep learning vision for heterogeneous network traffic control: Proposal, challenges, and future perspective
Recently, deep learning, an emerging machine learning technique, is garnering a lot of
research attention in several computer science areas. However, to the best of our …
research attention in several computer science areas. However, to the best of our …
Routing or computing? The paradigm shift towards intelligent computer network packet transmission based on deep learning
Recent years, Software Defined Routers (SDRs)(programmable routers) have emerged as a
viable solution to provide a cost-effective packet processing platform with easy extensibility …
viable solution to provide a cost-effective packet processing platform with easy extensibility …
A novel non-supervised deep-learning-based network traffic control method for software defined wireless networks
SDN has been regarded as the next-generation network paradigm as it decouples complex
network management from packet forwarding, which significantly simplifies the operation of …
network management from packet forwarding, which significantly simplifies the operation of …
Is machine learning ready for traffic engineering optimization?
G Bernárdez, J Suárez-Varela, A López… - 2021 IEEE 29th …, 2021 - ieeexplore.ieee.org
Traffic Engineering (TE) is a basic building block of the Internet. In this paper, we analyze
whether modern Machine Learning (ML) methods are ready to be used for TE optimization …
whether modern Machine Learning (ML) methods are ready to be used for TE optimization …
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 …
Deep reinforcement learning for router selection in network with heavy traffic
The rapid development of wireless communications brings a tremendous increase in the
amount number of data streams and poses significant challenges to the traditional routing …
amount number of data streams and poses significant challenges to the traditional routing …
Leveraging deep reinforcement learning for traffic engineering: A survey
After decades of unprecedented development, modern networks have evolved far beyond
expectations in terms of scale and complexity. In many cases, traditional traffic engineering …
expectations in terms of scale and complexity. In many cases, traditional traffic engineering …
Drl-or: Deep reinforcement learning-based online routing for multi-type service requirements
Emerging applications raise critical QoS requirements for the Internet. The improvements of
flow classification technologies, software defined networks (SDN), and programmable …
flow classification technologies, software defined networks (SDN), and programmable …