VNF Placement in Hybrid NFV Environment: Modeling and Genetic Algorithms

In this paper, we study the VNF placement problem in hybrid NFV environment, which is important during the transition from traditional networks to NFV networks. We first propose a new concept of hybrid NFV environment, which is more comprehensive and realistic than the former works. Then, we give ou...

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Bibliographic Details
Main Authors: Jiuyue Cao, Yan Zhang, Wei An, Xin Chen, Yanni Han, Jiyan Sun
Format: Conference Proceeding
Language:English
Subjects:
Conferences
Decision support systems
Encoding
genetic algorithm
Genetic algorithms
multi-objective optimization
Network Function Virtualization
Optimization
Sociology
Virtualization
VNF Placement
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Summary:In this paper, we study the VNF placement problem in hybrid NFV environment, which is important during the transition from traditional networks to NFV networks. We first propose a new concept of hybrid NFV environment, which is more comprehensive and realistic than the former works. Then, we give out a novel model of VNF placement optimization to achieve lower bandwidth consumption and lower maximum link utilization simultaneously, with consideration of VNF combination. Next, to solve this problem, we propose four genetic algorithms, which are combinations of the frameworks of two existing algorithms (MOGA and NSGA-II) and our novel modifications. Simulation results show that, in our 4 algorithms Greedy-NSGA-II has the best performance. When compared with other two non-genetic algorithms (BM and Random), the average total bandwidth consumption of Greedy-NSGA-II is only 12.24% and 2.96% of theirs respectively, and the average maximum link utilization of Greedy-NSGA-II is only 25.04% and 13.81% of theirs respectively.
ISSN:1521-9097
2690-5965
DOI:10.1109/ICPADS.2016.0105