Data modelling for the evaluation of virtualized network functions resource allocation algorithms

Rankothge, Windhya; Le, Franck; Russo, Alessandra; Lobo, Jorge

Data modelling for the evaluation of virtualized network functions resource allocation algorithms

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Citation

Rankothge W, Le F, Russo A, Lobo J. Data modelling for the evaluation of virtualized network functions resource allocation algorithms. 2017. 4 p.

Abstract

To conduct a more realistic evaluations on resource allocation algorithms for Virtualized Network Functions (VNFs), researches need data on: (1) potential Network Functions (NFs) chains (policies), (2) traffic flows passing through these NFs chains, (3) how the dynamic traffic changes affect the NFs (scale out/in) and (4) different data center architectures for the cloud infrastructure. However, there are no publicly available real data sets on NF chains and traffic that pass through NF chains. Therefore, we have used data from previous empirical analyses [1], [2] and made some assumptions to derive the required data to evaluate resource allocation algorithms for VNFs. We developed four programs to model the gathered data and generate the required data. All gathered data and data modelling programs are publicly available at [3]. We have used these data for our work in [4] and [5].

Related Publication/Data

Publicació relacionada: Rankothge W, Ma J, Le F, Russo A, Lobo J. Experimental results on the use of genetic algorithms for scaling virtualized network functions. In: 2015 IEEE Conference on Virtualization and Software Defined Network (NFV-SDN); 2015 Nov 18-21; San Francisco, CA. IEEE; 2015. p. 47-53. DOI 10.1109/NFV-SDN.2015.7387405 http://hdl.handle.net/10230/26036
http://hdl.handle.net/10230/26036

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