Control Oriented System Identification for Performance Management in Virtualized Software System

Capability to manage the performance of a shared resources environment relies on the model estimation of all dynamics in the system. The main challenge is to capture the nonlinear characteristic which inherently exists in software system applications. Hammerstein-Wiener block structural model is widely regarded as a basis for description of nonlinear systems. This paper extends the existing work in system identification of software systems using Hammerstein-Wiener block structural model. As part of the estimation, the linear element is represented in terms of Frequency Sampling Filter model and the inverse static output non-linearity is estimated using B-Spline curve functions. Experimental studies show that the static nonlinearities estimated when using the B-Spline functions have less oscillations and the overall model has a better performance than the case when using polynomial functions.