NDLI: An Online Algorithm for Dynamic NFV Placement in Cloud-Based Autonomous Response Networks

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An Online Algorithm for Dynamic NFV Placement in Cloud-Based Autonomous Response Networks

Content Provider	MDPI
Author	Cristina, Cervelló-Pastor Adriana, Fernández-Fernández Ochoa-Aday, Leonardo Grosso, Paola
Copyright Year	2018
Description	Autonomous response networks are becoming a reality thanks to recent advances in cloud computing, Network Function Virtualization (NFV) and Software-Defined Networking (SDN) technologies. These enhanced networks fully enable autonomous real-time management of virtualized infrastructures. In this context, one of the major challenges is how virtualized network resources can be effectively placed. Although this issue has been addressed before in cloud-based environments, it is not yet completely resolved for the online placement of virtual machines. For such a purpose, this paper proposes an online heuristic algorithm called Topology-Aware Placement of Virtual Network Functions (TAP-VNF) as a low-complexity solution for such dynamic infrastructures. As a complement, we provide a general formulation of the network function placement using the service function chaining concept. Furthermore, two metrics called consolidation and aggregation validate the efficiency of the proposal in the experimental simulations. We have compared our approach with optimal solutions, in terms of consolidation and aggregation ratios, showing a more suitable performance for dynamic cloud-based environments. The obtained results show that TAP-VNF also outperforms existing approaches based on traditional bin packing schemes.
Starting Page	163
e-ISSN	20738994
DOI	10.3390/sym10050163
Journal	Symmetry
Issue Number	5
Volume Number	10
Language	English
Publisher	MDPI
Publisher Date	2018-05-15
Access Restriction	Open
Subject Keyword	Symmetry Computation Theory and Mathematics Network Function Virtualization Cloud Dynamic Resource Provision Virtual Function Placement Software-defined Networking Bin Packing Algorithms Autonomous Response Networks.
Content Type	Text
Resource Type	Article

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