Online Scheduling in Virtualized TSN Networks via Joint Admission Control and VNF Embedding

被引:0
|
作者
Zhang, Yajing [1 ,2 ]
Chen, Cailian [1 ,2 ]
You, Chaoqun [3 ,5 ]
Li, Mingyan [1 ,2 ,4 ]
Guan, Xinping [1 ,2 ]
Quek, Tony Q. S.
机构
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
[2] Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
[3] Fudan Univ, Sch Comp Sci, Shanghai, Peoples R China
[4] Chongqing Univ, Coll Comp Sci, Chongqing 400044, Peoples R China
[5] Singapore Univ Technol & Design, Informat Syst Technol & Design, Singapore 487372, Singapore
基金
中国国家自然科学基金;
关键词
Time-sensitive Networking (TSN); Admission Control (AC); VNF embedding (VNE); Network Function Virtualization (NFV);
D O I
10.1109/ICCC62479.2024.10682035
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Introducing virtualization enhances the flexibility of time-sensitive networking (TSN), wherein applications manifest as service function chains comprising a series of virtual network functions (VNFs). However, such virtualized TSN realizes determinacy through global configuration, being too complicated to serve dynamic applications in time. To address this issue, we innovatively propose to achieve TSN scheduling by distributively executing admission control (AC), whereby the scheduling complexity is radically reduced. Specifically, we first build a two-way AC model that captures TSN multi-queue characteristics. Then, we define admissible regions of nodes and links, working as metrics for AC decision-making and enabling feasible TSN scheduling. Built upon this, we propose a joint AC and VNF embedding mechanism, Rapid Admission Control (RapidAC), which consists of two algorithms. The first algorithm responds to dynamic applications rapidly and derives nodemapping solutions by judging nodes' admissible regions. Based on this, the second algorithm augments the detailed VNF embedding solution according to admissible regions of links. Simulation results show that RapidAC reduces runtime by 90% compared with existing TSN scheduling algorithms.
引用
收藏
页数:6
相关论文
共 50 条
  • [21] Deep Reinforcement Learning-Based Joint Scheduling of 5G and TSN in Industrial Networks
    Zhu, Yuan
    Sun, Lei
    Wang, Jianquan
    Huang, Rong
    Jia, Xueqin
    ELECTRONICS, 2023, 12 (12)
  • [22] Swallow: Joint Online Scheduling and Coflow Compression in Datacenter Networks
    Zhou, Qihua
    Li, Peng
    Wang, Kun
    Zeng, Deze
    Guo, Song
    Guo, Minyi
    2018 32ND IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM (IPDPS), 2018, : 505 - 514
  • [23] Joint Online Coflow Routing and Scheduling in Data Center Networks
    Tan, Haisheng
    Jiang, Shaofeng H. -C.
    Li, Yupeng
    Li, Xiang-Yang
    Zhang, Chenzi
    Han, Zhenhua
    Lau, Francis Chi Moon
    IEEE-ACM TRANSACTIONS ON NETWORKING, 2019, 27 (05) : 1771 - 1786
  • [24] MIP-based Joint Scheduling and Routing with Load Balancing for TSN based In-vehicle Networks
    Syed, Ammad Ali
    Ayaz, Serkan
    Leinmueller, Tim
    Chandra, Madhu
    2020 IEEE VEHICULAR NETWORKING CONFERENCE (VNC), 2020,
  • [25] COMBINED ADMISSION CONTROL AND SCHEDULING IN MULTI-SERVICE NETWORKS
    Qiu Gongan Zhang Guoan Xu Chen Bao Zhihua (School of Electronics and Information
    JournalofElectronics(China), 2010, 27 (06) : 765 - 771
  • [26] Optimal Data Scheduling and Admission Control for Backscatter Sensor Networks
    Dinh Thai Hoang
    Niyato, Dusit
    Wang, Ping
    Kim, Dong In
    Le, Long Bao
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2017, 65 (05) : 2062 - 2077
  • [27] Joint scheduling and admission control for ATS-based switching nodes
    Hyman, Jay
    Lazar, Aurel A.
    Pacifici, Giovanni
    Computer Communications Review, 1992, 22 (04):
  • [28] Joint embedding of structure and features via graph convolutional networks
    Sébastien Lerique
    Jacob Levy Abitbol
    Márton Karsai
    Applied Network Science, 5
  • [29] Joint embedding of structure and features via graph convolutional networks
    Lerique, Sebastien
    Abitbol, Jacob Levy
    Karsai, Marton
    APPLIED NETWORK SCIENCE, 2020, 5 (01)
  • [30] Joint optimization of admission control and power control in cognitive radio networks
    Zhu J.
    Duan A.
    Xiong J.
    Chen H.
    1600, Chinese Institute of Electronics (39): : 641 - 648