Satellite communications have become an everyday aspect of our daily lives, and the current focus on satellite telecommunications is expected to continue to grow and gain greater prominence. On the other hand, implementing scheduled and unscheduled maintenance practices is essential to improving the availability and reliability of satellite systems. This paper presents a stochastic availability model designed through a Stochastic Petri Net (SPN) that considers the aging of satellites, offering support for infrastructure planning by integrating both scheduled and unscheduled maintenance considerations. Additionally, this research includes two case studies. The first case study explores an availability model that ignores the influence of aging, establishing a baseline of availability and second with aging. This baseline will be compared with the results obtained from the proposed SPN model, which incorporates the effects of aging. In this way, the behavior of both non-aging and aging variables can be analyzed to make contributions through the SPN that helps understand the availability of satellite systems.

Cloud-based architectures have grown in recent years, especially the interest in container-based solutions have sharply increased by enterprises worldwide. Containers are a form of lightweight virtualization that can be used to provide cloud services. Adopting this kind of technology in a bare- metal context is becoming strong because they can offer many benefits, like performance efficiency and costs reduction. Docker is a widespread platform for the creation and management of containers. As in any computational cloud service, Docker environments must deal with the intensive workload and may have a long-term life cycle, which might trigger some problems that compromise the system dependability. The software aging phenomenon is one of these likely problems. It is a process of cumulative errors or system misbehavior that leads to application failures and performance degradation throughout its runtime. This paper aims to monitor and evaluate software aging effects on the Docker platform in a cloud computing environment. We conducted two experimental studies with automated workloads to simulate containers' life cycle and the intensive use of Docker features, while the system was monitored. The results show high resource consumption by the operating system's network utility, in addition to memory fragmentation in the sub-processes of the Docker platform. Trends of increasing resident memory consumption were also observed in one of these scenarios.