A Study on Reinforcement Learning-Based Traffic Engineering in Software-Defined Networks
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-3035-5_4
Reference33 articles.
1. Xu Z, Tang J, Meng J, Zhang W, Wang Y, Liu CH, Yang D (2018) Experience-driven networking: a deep reinforcement learning based approach. In: IEEE INFOCOM 2018-IEEE conference on computer communications. IEEE, pp 1871–1879
2. Wu T, Zhou P, Wang B, Li A, Tang X, Xu Z, Ding X (2020) Joint traffic control and multi-channel reassignment for core backbone network in SDN-IoT: a multi-agent deep reinforcement learning approach. IEEE Trans Netw Sci Eng 8(1):231–245
3. Sun P, Lan J, Li J, Zhang J, Hu Y, Guo Z (2020) A scalable deep reinforcement learning approach for traffic engineering based on link control. IEEE Commun Lett 25(1):171–175
4. https://www.fiber-optic-cable-sale.com/will-sdn-change-future-network.html
5. Zhang J, Ye M, Guo Z, Yen CY, Chao HJ (2020) CFR-RL: Traffic engineering with reinforcement learning in SDN. IEEE J Sel Areas Commun 38(10):2249–2259
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