NDLI: Optimised approach for VNF embedding in NFV

Content Provider	IET Digital Library
Author	Yi, Bo Wang, Xingwei Huang, Min
Abstract	The Virtual Network Function (VNF) embedding problem is important for service provision in the context of Network Function Virtualisation (NFV). However, this problem is proved to be NP-hard and challenging, and requires to be explored further. In this study, the authors first formulate it as an Integer Linear Programming (ILP) model for optimal solutions. Then, to compensate for the high running time of solving the ILP model, they propose a heuristic approach which fulfils the embedding process by jointly taking the global network connectivity and the local substrate node capacity into consideration. The simulation on real-world network topologies demonstrates that the proposed approach can provide solutions within 1.7 times of the optimal solution offered by ILP. In addition, the experiments also suggest that the proposed approach can provide up to 2.75 times reduction in the overall cost than the other benchmarks.
Starting Page	2630
Ending Page	2638
Page Count	9
ISSN	17518628
Volume Number	12
e-ISSN	17518636
Issue Number	Issue 20, Dec (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/12/20
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2018.5509
Journal	IET Communications
Publisher Date	2018-09-26
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Communication Computer Network And Technique Global Network Connectivity ILP Model Integer Linear Programming Model Integer Programming Linear Programming Local Substrate Node Capacity Network Function Virtualisation NFV NP-hard Optimisation Technique Optimised Approach Real-world Network Topology Telecommunication Network Topology Virtual Network Function Embedding Problem Virtualisation VNF Embedding
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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