[1] |
刘辰屹, 徐明伟, 耿男, 等. 基于机器学习的智能路由算法综述[J]. 计算机研究与发展, 2020, 57(4):671-687.
|
[2] |
欧阳晔, 王立磊, 杨爱东, 等. 通信人工智能的下一个十年[J]. 电信科学, 2021, 37(3):1-36.
doi: 10.11959/j.issn.1000-0801.2021055
|
[3] |
CONG N L, THAI D H, GONG S. Applications of deep reinforcement learning in communications and networking: a survey[J]. IEEE Communications Surveys & Tutorials, 2019, 21(4):3133-3174.
|
[4] |
VINAYAKUMAR R, SOMAN K. P, POORNACHANDRAN P. Applying deep learning approaches for network traffic prediction[C]// 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI). India: IEEE, 2017:2353-2358.
|
[5] |
RAMAKRISHNAN N, SONI T. Network traffic prediction using recurrent neural networks[C]// 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA). Orlando, FL, USA: IEEE, 2018:187-193.
|
[6] |
HUA Y, ZHAO Z, LI R, et al. Deep learning with long short-term memory for time series prediction[J]. IEEE Communications Magazine, 2019, 57(6):114-119.
doi: 10.1109/MCOM.2019.1800155
|
[7] |
THEYAZN H,. H A, MELFI A, AHMED A A, et al. Intelligent hybrid model to enhance time series models for predicting network traffic[J]. IEEE Access, 2020(8):130431-130451.
|
[8] |
HE K, CHEN X, WU Q, et al. Graph attention spatial-temporal network with collaborative global-local learning for citywide mobile traffic prediction[J]. IEEE Transactions on Mobile Computing, 2020, 21(4):1244-1256.
doi: 10.1109/TMC.2020.3020582
URL
|
[9] |
SILVER D, LEVER G, HEESS N, et al. Deterministic policy gradient algorithms[C]// International Conference on Machine Learning. Beijing: JMLR.org, 2014:387-395.
|
[10] |
LILLICRAP T P, HUNT J J, PRITZEL A, et al. Continuous control with deep reinforcement learning[J]. ArXiv Preprint ArXiv:1509.02971, 2015.
|
[11] |
ZHU H, VARUN G, SATYAJEET S A, et al. Network planning with deep reinforcement learning[C]// Proceedings of the 2021 ACM SIGCOMM 2021 Conference (SIGCOMM’21). New York, NY, USA: Association for Computing Machinery, 2021:258-271.
|
[12] |
胡道允, 齐进, 陆钱春, 等. 基于深度学习的流量工程算法研究与应用[J]. 电信科学, 2021, 37(2): 107-114.
doi: 10.11959/j.issn.1000-0801.2021027
|
[13] |
兰巨龙, 张学帅, 胡宇翔, 等. 基于深度强化学习的软件定义网络QoS优化[J]. 通信学报, 2019, 40(12): 60-67.
doi: 10.11959/j.issn.1000-436x.2019227
|
[14] |
ZHANG J, YE M, GUO Z. CFR-RL:traffic engineering with reinforcement learning in SDN[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(10): 2249-2259.
doi: 10.1109/JSAC.49
URL
|
[15] |
SUN S, KIRAN M, REN W. MAMRL: exploiting multi-agent meta reinforcement learning in WAN traffic engineering[J]. ArXiv Preprint ArXiv:2111.15087, 2021.
|