Daniel Godfrey1, Beom-Su Kim1, Haoran Miao1, Babar Shah2, Bashir Hayat3, Imran Khan4, Tae-Eung Sung5, Ki-Il Kim1,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3671-3692, 2021, DOI:10.32604/cmc.2021.017475
- 06 May 2021
Abstract The end-to-end delay in a wired network is strongly dependent on congestion on intermediate nodes. Among lots of feasible approaches to avoid congestion efficiently, congestion-aware routing protocols tend to search for an uncongested path toward the destination through rule-based approaches in reactive/incident-driven and distributed methods. However, these previous approaches have a problem accommodating the changing network environments in autonomous and self-adaptive operations dynamically. To overcome this drawback, we present a new congestion-aware routing protocol based on a Q-learning algorithm in software-defined networks where logically centralized network operation enables intelligent control and management of network resources.… More >
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