AN EFFICIENT LINEAR PROGRAMMING ROUNDING-AND-REFINEMENT ALGORITHM FOR LARGE-SCALE NETWORK SLICING PROBLEM

被引:5
作者
Chen, Wei-Kun [1 ]
Liu, Ya-Feng [2 ]
Dai, Yu-Hong [2 ]
Luo, Zhi-Quan [3 ,4 ]
机构
[1] Beijing Inst Technol, Sch Math & Stat, Beijing, Peoples R China
[2] Chinese Acad Sci, AMSS, ICMSEC, LSEC, Beijing, Peoples R China
[3] Shenzhen Res Inst Big Data, Shenzhen, Peoples R China
[4] Chinese Univ Hong Kong, Shenzhen, Peoples R China
来源
2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021) | 2021年
关键词
LP Relaxation; Network Slicing; Resource Allocation; Rounding-and-Refinement; DEPLOYMENT;
D O I
10.1109/ICASSP39728.2021.9413378
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
In this paper, we consider the network slicing problem which attempts to map multiple customized virtual network requests (also called services) to a common shared network infrastructure and allocate network resources to meet diverse service requirements, and propose an efficient two-stage algorithm for solving this NP-hard problem. In the first stage, the proposed algorithm uses an iterative linear programming (LP) rounding procedure to place the virtual network functions of all services into cloud nodes while taking traffic routing of all services into consideration; in the second stage, the proposed algorithm uses an iterative LP refinement procedure to obtain a solution for traffic routing of all services with their end-to-end delay constraints being satisfied. Compared with the existing algorithms which either have an exponential complexity or return a low-quality solution, our proposed algorithm achieves a better trade-off between solution quality and computational complexity. In particular, the worst-case complexity of our proposed algorithm is polynomial, which makes it suitable for solving large-scale problems. Numerical results demonstrate the effectiveness and efficiency of our proposed algorithm.
引用
收藏
页码:4735 / 4739
页数:5
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