Cross-Platform Estimation of Network Function Performance

Abstract

This work shows how the performance of a network function can be estimated with an error margin that is small enough to properly support orchestration of network functions virtualization (NFV) platforms. Being able to estimate the performance of a virtualized network function (VNF) on execution hardware of various types enables its optimal placement, while efficiently utilizing available resources. Network functions are modeled using a methodology focused on the identification of recurring execution patterns and aimed at providing a platform independent representation. By mapping the model on specific hardware, the performance of the network function can be estimated in terms of maximum throughput that the network function can achieve on the specific execution platform. The approach is such that once the basic modeling building blocks have been mapped, the estimate can be computed automatically. This work presents the model of an Ethernet switch and evaluates its accuracy by comparing the performance estimation it provides with experimental results.