Modeling and analysis of software rejuvenation in a server virtualized system

As server virtualization is used as an essential software infrastructure of various software services such as cloud computing, availability management of server virtualized system is becoming more significant. Although time-based software rejuvenation is useful to postpone/prevent failures due to software aging in a server virtualized system, the rejuvenation schedules for virtual machine (VM) and virtual machine monitor (VMM) need to be determined in a proper way for the VM availability, since VMM rejuvenation affects VMs running on the VMM. This paper presents analytic models using stochastic reward nets for three time-based rejuvenation techniques of VMM; (i) Cold-VM rejuvenation in which all VMs are shut down before the VMM rejuvenation, (ii) Warm-VM rejuvenation in which all VMs are suspended before the VMM rejuvenation and (iii) Migrate-VM rejuvenation in which all VMs are moved to the other host server during the VMM rejuvenation. We compare the three techniques in terms of steady-state availability and the number of transactions lost in a year. We find the optimal combination of rejuvenation trigger intervals for each rejuvenation technique by a gradient search method. The numerical analysis shows the interesting result that Warm-VM rejuvenation does not always outperform Cold-VM rejuvenation in terms of steady-state availability depending on rejuvenation trigger intervals. Migrate-VM rejuvenation is better than the other two as long as live VM migration rate is large enough and the other host server has a capacity to accept the migrated VM.