Joint Virtual Network Topology Design and Embedding for Cybertwin-Enabled 6G Core Networks

被引:20
作者
Li, Junling [1 ,2 ]
Shi, Weisen [2 ]
Ye, Qiang [3 ]
Zhang, Shan [4 ]
Zhuang, Weihua [2 ]
Shen, Xuemin [2 ]
机构
[1] Univ Waterloo, Shenzhen Inst Artificial Intelligence & Robot Soc, Waterloo, ON N2L 3G1, Canada
[2] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
[3] Minnesota State Univ, Dept Elect & Comp Engn & Technol, Mankato, MN 56001 USA
[4] Beihang Univ, Sch Comp Sci & Engn, Beijing 100191, Peoples R China
基金
中国国家自然科学基金; 加拿大自然科学与工程研究理事会;
关键词
Delays; Resource management; Quality of service; Topology; Substrates; Internet of Things; Network servers; 6G; cybertwin; end-to-end (E2E) packet delay; network virtualization (NV); resource allocation; topology; virtual network embedding (VNE);
D O I
10.1109/JIOT.2021.3097053
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To efficiently allocate heterogeneous resources for customized services, in this article, we propose a network virtualization (NV)-based network architecture in cybertwin-enabled 6G core networks. In particular, we investigate how to optimize the virtual network (VN) topology (which consists of several virtual nodes and a set of intermediate virtual links) and determine the resultant VN embedding in a joint way over a cybertwin-enabled substrate network. To this end, we formulate an optimization problem whose objective is to minimize the embedding cost, while ensuring that the end-to-end (E2E) packet delay requirements are satisfied. The queueing network theory is utilized to evaluate each service's E2E packet delay, which is a function of the resources assigned to the virtual nodes and virtual links for the embedded VN. We reveal that the problem under consideration is formally a mixed-integer nonlinear program (MINLP) and propose an improved brute-force search algorithm to find its optimal solutions. To enhance the algorithm's scalability and reduce the computational complexity, we further propose an adaptively weighted heuristic algorithm to obtain near-optimal solutions to the problem for large-scale networks. Simulations are conducted to show that the proposed algorithms can effectively improve network performance compared to other benchmark algorithms.
引用
收藏
页码:16313 / 16325
页数:13
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