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Availability‐aware virtual network function placement based on multidimensional universal generating functions

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  • Kengo Arakawa
  • Eiji Oki

Abstract

Network function virtualization (NFV) implements network functions as software, which enables flexible, resource‐efficient, and rapid provision of network services. In NFV, network services are realized by the service function chain (SFC), which is a chain of virtual network functions (VNFs) linked in the proper order. Both availability and deployment cost are key concerns for network operators providing network services as SFC. This paper proposes a flexible VNF placement model on a per‐VNF instance basis that minimizes deployment costs while satisfying availability requirements that may be placed on SFC. This paper uses a multidimensional universal generating function (MUGF) method, which is a multistate system analysis method, to compute the availability of a multistate SFC system with multiple VNFs coexisting on a server. The MUGF method calculates the performance of the entire SFC by combining the performance of servers as determined by applying a continuous‐time Markov chain. To reduce the time to compute the SFC availability, we introduce operators to be applied to MUGF and develop an availability computing method. In addition, a heuristic algorithm for determining VNF placement targeting the lowest deployment cost possible while meeting availability requirements is presented. Numerical results show that the proposed model obtains VNF placement with lower cost than the conventional model in all examined cases. The proposed model achieves VNF placement at 58.5%–75.0% of the deployment cost of the conventional model for the same SFC availability requirements.

Suggested Citation

  • Kengo Arakawa & Eiji Oki, 2024. "Availability‐aware virtual network function placement based on multidimensional universal generating functions," International Journal of Network Management, John Wiley & Sons, vol. 34(2), March.
  • Handle: RePEc:wly:intnem:v:34:y:2024:i:2:n:e2252
    DOI: 10.1002/nem.2252
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