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 …
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 …
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 …
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 …
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 …
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 …
TIDE: Time-relevant deep reinforcement learning for routing optimization
Routing optimization has been researched in network design for a long time, and plenty of
optimization schemes have been proposed from both academia and industry. However …
optimization schemes have been proposed from both academia and industry. However …
DRSIR: A deep reinforcement learning approach for routing in software-defined networking
DM Casas-Velasco, OMC Rendon… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traditional routing protocols employ limited information to make routing decisions, which
leads to slow adaptation to traffic variability and restricted support to the quality of service …
leads to slow adaptation to traffic variability and restricted support to the quality of service …
A deep-reinforcement learning approach for software-defined networking routing optimization
G Stampa, M Arias, D Sánchez-Charles… - arXiv preprint arXiv …, 2017 - arxiv.org
In this paper we design and evaluate a Deep-Reinforcement Learning agent that optimizes
routing. Our agent adapts automatically to current traffic conditions and proposes tailored …
routing. Our agent adapts automatically to current traffic conditions and proposes tailored …
Toward packet routing with fully distributed multiagent deep reinforcement learning
Packet routing is one of the fundamental problems in computer networks in which a router
determines the next-hop of each packet in the queue to get it as quickly as possible to its …
determines the next-hop of each packet in the queue to get it as quickly as possible to its …