A Single-Hop Selection Strategy of VNFs Based on Traffic Classification in NFV

  • Bo HeEmail author
  • Jingyu Wang
  • Qi Qi
  • Haifeng Sun
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 268)


Network Function Virtualization (NFV) has become a hot technology since it provides the flexible management of network functions and efficient sharing of network resources. Network resources in NVF require an appropriate management strategy which often manifests as a difficult online decision making task. Resource management in NFV can be thought of as a process of virtualized network functions (VNFs) selection or deployment. This paper proposes a single-hop VNFs selection strategy to realize network resource management. For satisfying quality requirements of different network services, this strategy is based on the results of traffic classification which utilizes Multi-Grained Cascade Forest (gcForest) to distinguish user behaviors on the internet. In the order of VNFs, a network is divided into several layers where each arrived packet needs to queue. The scheduler of each layer selects a layer which hosts the next VNF for the packets in the queue. Experiments prove that the proposed traffic classification method increases the precision by 7.7% and improves the real-time performance. The model of VNFs selection reduces network congestion compared to traditional single-hop scheduling models. Moreover, the number of packets which fail to reach target node in time drops 30% to 50% using the proposed strategy compared to the strategy without the section of traffic classification.


NFV Traffic classification Resource management VNFs selection 



This work was jointly supported by: (1) National Natural Science Foundation of China (No. 61771068, 61671079, 61471063, 61372120, 61421061); (2) Beijing Municipal Natural Science Foundation (No. 4182041, 4152039); (3) the National Basic Research Program of China (No. 2013CB329102).


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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijingChina

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