GraphNET: Graph Neural Networks for routing optimization in Software Defined Networks

In this paper, a graph neural net-based routing algorithm is designed which leverages global information from controller of a software-defined network to predict optimal path with minimum average delay between source and destination nodes in software-defined networks. Graph nets are used because of...

Celý popis

Podrobná bibliografie

Vydáno v:	Computer communications Ročník 178; s. 169 - 182
Hlavní autoři:	Swaminathan, Avinash, Chaba, Mridul, Sharma, Deepak Kumar, Ghosh, Uttam
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.10.2021
Témata:	Deep Q-learning Deep Reinforcement Learning Graph Neural Networks Q-table Routing algorithm Routing optimization Software-Defined Networking Q-table Routing algorithm Software-Defined Networking Deep Reinforcement Learning Routing optimization Deep Q-learning Graph Neural Networks
ISSN:	0140-3664, 1873-703X
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!