CFR-RL: Traffic engineering with reinforcement learning in SDN

J Zhang, M Ye, Z Guo, CY Yen… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
Traditional Traffic Engineering (TE) solutions can achieve the optimal or near-optimal
performance by rerouting as many flows as possible. However, they do not usually consider …
被引用次数：144 相关文章

CFR-RL: Traffic Engineering with Reinforcement Learning in SDN

J Zhang, M Ye, Z Guo, CY Yen, HJ Chao - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
Abstract Traditional Traffic Engineering (TE) solutions can achieve the optimal or near-
optimal performance by rerouting as many flows as possible. However, they do not usually …

CFR-RL: Traffic Engineering with Reinforcement Learning in SDN

J Zhang, M Ye, Z Guo, CY Yen… - IEEE Journal on …, 2020 - nyuscholars.nyu.edu
Abstract Traditional Traffic Engineering (TE) solutions can achieve the optimal or near-
optimal performance by rerouting as many flows as possible. However, they do not usually …

CFR-RL: Traffic Engineering with Reinforcement Learning in SDN

J Zhang, M Ye, Z Guo, CY Yen, HJ Chao - arXiv preprint arXiv:2004.11986, 2020 - arxiv.org
Traditional Traffic Engineering (TE) solutions can achieve the optimal or near-optimal
performance by rerouting as many flows as possible. However, they do not usually consider …

CFR-RL: TRAFFIC ENGINEERING WITH REINFORCEMENT LEARNING IN SDN

LC Wang - infonews-fornthu.nycu.edu.tw
Traffic Engineering (TE) is one of important network features for Software-Defined
Networking (SDN) with an aim to help Internet Service Providers (ISPs) optimize network …