Server virtualization is an essential component in virtualized software infrastructure such as cloud computing. Virtual machines are generated through a software called virtual machine monitor (VMM) running on physica...Server virtualization is an essential component in virtualized software infrastructure such as cloud computing. Virtual machines are generated through a software called virtual machine monitor (VMM) running on physical servers. The risks of software aging caused by aging-related bugs affect both VM and VMM. As a result, service reliability degrades may generate huge financial losses to companies. This paper presents an analytic model using stochastic reward nets for time-based rejuvenation techniques of VMM and VM. We propose to manipulate the VM behavior while the VMM rejuvenation is according to the load on the system. Using a previous Petri net model of virtualized server, we performed an algorithm in order to optimize rejuvenation technique and achieve high availability. So we perform Migrate-VM rejuvenation or Warm-VM rejuvenation while there are current jobs in the system. Although Migrate-VM rejuvenation is better than Warm-VM rejuvenation in steady state availability, it can’t be always performed as it depends on the capacity of the other host. When the queue is empty and the virtual machine has no current jobs to serve, we propose to combine both VMM rejuvenation and VM rejuvenation. We show that the proposed technique can enhance the availability of VMs.展开更多
文摘Server virtualization is an essential component in virtualized software infrastructure such as cloud computing. Virtual machines are generated through a software called virtual machine monitor (VMM) running on physical servers. The risks of software aging caused by aging-related bugs affect both VM and VMM. As a result, service reliability degrades may generate huge financial losses to companies. This paper presents an analytic model using stochastic reward nets for time-based rejuvenation techniques of VMM and VM. We propose to manipulate the VM behavior while the VMM rejuvenation is according to the load on the system. Using a previous Petri net model of virtualized server, we performed an algorithm in order to optimize rejuvenation technique and achieve high availability. So we perform Migrate-VM rejuvenation or Warm-VM rejuvenation while there are current jobs in the system. Although Migrate-VM rejuvenation is better than Warm-VM rejuvenation in steady state availability, it can’t be always performed as it depends on the capacity of the other host. When the queue is empty and the virtual machine has no current jobs to serve, we propose to combine both VMM rejuvenation and VM rejuvenation. We show that the proposed technique can enhance the availability of VMs.
