Machine learning-based actuation orchestration for inter-/intra-data center networks

被引:0
作者
Spadaro, Salvatore [1 ]
Pages, Albert [1 ]
Agraz, Fernando [1 ]
机构
[1] UPC, GCO, Barcelona, Spain
来源
2023 INTERNATIONAL CONFERENCE ON PHOTONICS IN SWITCHING AND COMPUTING, PSC | 2023年
关键词
Datacenters; optical networks; quality assurance; orchestration; machine learning;
D O I
10.1109/PSC57974.2023.10297194
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Datacenter (DC) infrastructures are essential to support the requirements posed by nowadays digital society and emerging industrial trends. In such context, a proper actuation management has become especially relevant for service quality assurance operations. In situations where it may be difficult to determine which is the sub-system that needs to apply an actuation, machine learning (ML)-based strategies become valuable assets to orchestrate the actuations to be applied. In this paper, we discuss three strategies for actuation orchestration in inter-/intra-DC scenarios interconnected through optical network systems and benchmark them in terms of requirements that they impose and the achieved performance.
引用
收藏
页数:3
相关论文
共 6 条
  • [1] [Anonymous], 2020, CISCO ANN INTERNET R
  • [2] Cisco, 2022, 2022 Global Hybrid Cloud Trends Report
  • [3] El Hakim A., 2019, White paper
  • [4] Transfer Reinforcement Learning Aided Distributed Network Slicing Optimization in Industrial IoT
    Mai, Tianle
    Yao, Haipeng
    Zhang, Ni
    He, Wenji
    Guo, Dong
    Guizani, Mohsen
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2022, 18 (06) : 4308 - 4316
  • [5] Pages A., 2022, IEEE TRANS NETW SERV
  • [6] Scaling Optical Interconnects for Hyperscale Data Center Networks
    Xie, Chongjin
    Zhang, Bo
    [J]. PROCEEDINGS OF THE IEEE, 2022, 110 (11) : 1699 - 1713