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Cloud computing has been applied to various purposes going from commercial systems to real-time applications, such as video streaming. Downtime and service outage brings financial losses to Cloud providers and may damage their reputation. Therefore, the availability is one of the main challenges to turn Cloud more reliable. Systems managers need mechanisms to estimate the system availability in order to define SLAs with more property. One of the issues that affect the availability of Cloud system is software aging. This problem promotes a gradual performance and reliability degradation of the applications hosted on a Cloud. This dissertation proposes a set of availability models to Cloud with rejuvenation enabled by VM migration. The methodology adopted emphasizes models construction, which is based on models for a basic infrastructure of a Cloud (FrontEnd, node and VM) validated by injection of faults and repairs in a real testbed. Aging experiments are also made in a real environment. Closed formulas were generated by means of basic infrastructure cloud models considering a sensitivity analysis. Experiments are performed in order to indicate the behavior of aging and the effectiveness of the rejuvenation method proposed. From this, a hierarchical model is proposed based on RBD and SPN capable of representing different schedules of migrating VMs for rejuvenation. The aging experiments conducted were able to achieve highlight effects caused by this phenomenon. Moreover, the rejuvenation tests depict the effective method used for aging detected. The case studies show the applicability of the proposed models. Initially, it is possible to conclude that, considering the operational and failure modes, the FrontEnd is the most critical component to the availability of basic infrastructure. And that considering the environment studied, the repair time is more sensitive than the failure to stationary availability. Based on SPN model is possible to conclude that the correct scheduling migrations can involve significant gains in the system availability, especially in those who are submitted the most intensive workloads.

Modelos de Disponibilidade para Nuvens Privadas: Rejuvenescimento de Software Habilitado por Agendamento de Migração de VMs