Reconfigurable Network Topology Based on Deep Reinforcement Learning in Software-Defined Data-Center Networks

被引：0
|
作者：
Yang, Wen [1 ]
Guo, Bingli [1 ]
Shang, Yu [2 ]
Huang, Shanguo [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Sch Elect Engn, State Key Lab Informat Photon & Opt Commun, Beijing, Peoples R China
[2] Cyberspace Secur Key Lab Sichuan Prov, Chengdu 610041, Peoples R China
来源：
2020 ASIA COMMUNICATIONS AND PHOTONICS CONFERENCE (ACP) AND INTERNATIONAL CONFERENCE ON INFORMATION PHOTONICS AND OPTICAL COMMUNICATIONS (IPOC) | 2020年
关键词：
D O I：
暂无
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
In this paper, a Deep-Reinforcement Learning (DRL) agent is implemented and evaluated to enable dynamic topology reconfiguration according to traffic fluctuations and proposes to minimize the network delay. (C) 2020 The Author(s)
引用
收藏
页数：3
相关论文
共 50 条
  • [31] Deep learning for the security of software-defined networks: a review
    Taheri, Roya
    Ahmed, Habib
    Arslan, Engin
    [J]. CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2023, 26 (05): : 3089 - 3112
  • [32] Deep learning for the security of software-defined networks: a review
    Roya Taheri
    Habib Ahmed
    Engin Arslan
    [J]. Cluster Computing, 2023, 26 : 3089 - 3112
  • [33] Software-Defined Data Center
    Ghazanfar Ali
    Jie Hu
    Bhumip Khasnabish
    [J]. ZTE Communications, 2013, 11 (04) : 2 - 7
  • [34] Application of Software-Defined Network with Software-based Architecture in Enterprise Data Center
    Yu, Kean
    Yu, Cong
    Wang, Tingting
    Fan, Jiang
    Li, Yan
    [J]. 2016 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY PROCEEDINGS - CYBERC 2016, 2016, : 500 - 505
  • [35] Deep Reinforcement Learning Application for Network Latency Management in Software Defined Networks
    Bouzidi, El Hocine
    Outtagarts, Abdelkader
    Langar, Rami
    [J]. 2019 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2019,
  • [36] Deep Graph Reinforcement Learning Based Intelligent Traffic Routing Control for Software-Defined Wireless Sensor Networks
    Huang, Ru
    Guan, Wenfan
    Zhai, Guangtao
    He, Jianhua
    Chu, Xiaoli
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (04):
  • [37] Reconfigurable and software-defined networks of connectors and components
    [J]. 2015, Springer Verlag (8998):
  • [38] DeepPlace: Deep reinforcement learning for adaptive flow rule placement in Software-Defined IoT Networks
    Tri Gia Nguyen
    Phan, Trung, V
    Dinh Thai Hoang
    Hai Hoang Nguyen
    Duc Tran Le
    [J]. COMPUTER COMMUNICATIONS, 2022, 181 : 156 - 163
  • [39] Reconfigurable Network Systems and Software-Defined Networking
    Zilberman, Noa
    Watts, Philip M.
    Rotsos, Charalampos
    Moore, Andrew W.
    [J]. PROCEEDINGS OF THE IEEE, 2015, 103 (07) : 1102 - 1124
  • [40] Software-Defined Networks with Mobile Edge Computing and Caching for Smart Cities: A Big Data Deep Reinforcement Learning Approach
    He, Ying
    Yu, F. Richard
    Zhao, Nan
    Leung, Victor C. M.
    Yin, Hongxi
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2017, 55 (12) : 31 - 37
12345