Cost-Efficient Service Function Chain Orchestration for Low-Latency Applications in NFV Networks

被引:2
作者
Sun, Gang [1 ,2 ]
Zhu, Gungyang [1 ]
Liao, Dan [1 ]
Yu, Hongfang [1 ,2 ]
Du, Xiaojiang [3 ]
Guizani, Mohsen [4 ]
机构
[1] Univ Elect Sci & Technol China, Key Lab Opt Fiber Sensing & Commun, Minist Educ, Chengdu 611731, Sichuan, Peoples R China
[2] Univ Elect Sci & Technol China, Ctr Cyber Secur, Chengdu 611731, Sichuan, Peoples R China
[3] Temple Univ, Dept Comp & Informat Sci, Philadelphia, PA 19122 USA
[4] Univ Idaho, Dept Elect & Comp Engn, Moscow, ID 83844 USA
来源
IEEE SYSTEMS JOURNAL | 2019年 / 13卷 / 04期
基金
中国国家自然科学基金;
关键词
Machine learning; network function virtualization; provisioning; service function chain; VIRTUAL NETWORK; ENERGY-EFFICIENT; CHALLENGES; FRAMEWORK;
D O I
10.1109/JSYST.2018.2879883
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the popularization and development of cloud computing, network function virtualization and service function chain (SFC) provisioning have attracted increasing attention from researchers. Excellent and reliable network service is important for network development. Moreover, as the number of network users increases, network service construction costs become very high. Therefore, an efficient algorithm is necessary to provide an SFC with excellent performance and low resource costs. In this paper, we re-examine the problem of optimizing the deployment of an SFC to provide users with excellent and resource-saving network service. We propose a heuristic, closed-loop feedback (CLF) algorithm to find the shortest path to map an SFC. To solve the problem, we introduce and integrate a restricted Boltzmann machine and cross entropy to improve the performance of CLF. Simulation results demonstrate the excellent performance of CLF. The communication delay is reduced by approximately 20%, the accept ratio improves by approximately 15%, and the algorithm running time decreases by approximately 20%. In addition, the resource utilization ratio increases by approximately 15%, and the resource fragmentation ratio decreases by approximately 50%.
引用
收藏
页码:3877 / 3888
页数:12
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