Dynamic system characterization of enterprise servers via nonparametric identification

Dynamic characterization and fault detection are carried out in enterprise servers using nonparametric identification techniques based on sinusoidal excitation. The introduction of subtle sinusoidal perturbations in computer load variables or physical variables allows us to obtain a dynamic input-output characterization in the frequency domain. The input-output relationship is described in terms of coupling coefficients between a wide variety of physical and performance variables at different selected frequencies. This innovative approach in the field of computer science, based on a well-known system identification technique, has been demonstrated in empirical studies to provide valuable dynamic system characterization information that can be indispensable to datacenter operations personnel for the functions of performance management, capacity planning, quality-of-service (QoS) assurance, dynamic resource provisioning, and root cause analyses.