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
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