Performance Modeling of Softwarized Network Services Based on Queuing Theory with Experimental Validation Prados Garzón, Jonathan Ameigeiras Gutiérrez, Pablo José Ramos Muñoz, Juan José Navarro Ortiz, Jorge Andres-Maldonado, Pilar López Soler, Juan Manuel Network Softwarization NFV performance modeling queuing theory queuing model softwairzed network services resource dimensioning dynamic resource provisioning Network Functions Virtualization facilitates the automation of the scaling of softwarized network services (SNSs). However, the realization of such a scenario requires a way to determine the needed amount of resources so that the SNSs performance requisites are met for a given workload. This problem is known as resource dimensioning, and it can be efficiently tackled by performance modeling. In this vein, this paper describes an analytical model based on an open queuing network of G/G/m queues to evaluate the response time of SNSs. We validate our model experimentally for a virtualized Mobility Management Entity (vMME) with a three-tiered architecture running on a testbed that resembles a typical data center virtualization environment. We detail the description of our experimental setup and procedures. We solve our resulting queueing network by using the Queueing Networks Analyzer (QNA), Jackson’s networks, and Mean Value Analysis methodologies, and compare them in terms of estimation error. Results show that, for medium and high workloads, the QNA method achieves less than half of error compared to the standard techniques. For low workloads, the three methods produce an error lower than 10%. Finally, we show the usefulness of the model for performing the dynamic provisioning of the vMME experimentally. 2020-02-17T07:19:14Z 2020-02-17T07:19:14Z 2019-12-25 journal article J. Prados, P. Ameigeiras, J. J. Ramos-Munoz, J. Navarro-Ortiz, P. Andres-Maldonado and J. M. Lopez-Soler, "Performance Modeling of Softwarized Network Services Based on Queuing Theory with Experimental Validation," in IEEE Transactions on Mobile Computing. http://hdl.handle.net/10481/59700 10.1109/TMC.2019.2962488 eng info:eu-repo/grantAgreement/EC/H2020/871428 This work has been partially funded by the H2020 research and innovation project 5G-CLARITY (Grant No. 871428), national research project 5G-City: TEC2016-76795-C6-4-R, and the Spanish Ministry of Education, Culture and Sport (FPU Grant 13/04833). http://creativecommons.org/licenses/by-nc-nd/3.0/es/ open access Atribución-NoComercial-SinDerivadas 3.0 España Institute of Electrical and Electronics Engineers (IEEE)