Name
Title | ||
|---|---|---|
Reinforcement Learning-Driven QoS-Aware Intelligent Routing for Software-Defined Networks |
Abstract | ||
|---|---|---|
Software-defined network (SDN) is an emerging computer networking technology that disjoints the data forwarding from the centralized control and enables a highly manageable and flexible networking paradigm. There has been intensive research developed for efficient routing and resource allocation for SDNs. However, there still remain essential challenges to achieve situation-awareness networking management to ensure the application-driven Quality-of-Service (QoS) even in the presence of cyber attacks. To address this issue, in this paper, we exploit reinforcement learning (RL) technologies to develop a situation-awareness and intelligent networking management from the perspective of routing management. The performance of our proposed RL-enabled routing management method is evaluated in the simulation sections by considering various scenarios. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/GlobalSIP45357.2019.8969320 | 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) |
Keywords | Field | DocType |
SDN,Advantage Actor-Critic(A2C) Reinforcement Learning,Computer Network,QoS. | Qos aware,Computer science,Quality of service,Computer network,Exploit,Resource allocation,Software-defined networking,Reinforcement learning | Conference |
ISSN | ISBN | Citations |
2376-4066 | 978-1-7281-2724-8 | 0 |
PageRank | References | Authors |
0.34 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Md Billal Hossain | 1 | 0 | 0.68 |
| Wei Jin | 2 | 83 | 25.25 |