For several years, cloud computing systems have been generating debate and interest within IT corporations. These cloud computing environments provide storage and processing systems that are adaptable, efficient and simple, thus allowing for rapid infrastructure modifications to be made, according to constantly changing workloads. Organizations of any size and type are migrating to the cloud supporting solutions based on Web. Due to the benefits of the pay-per-use model and scalability factors, services such as Video Streaming. Recent failure events in Video Streaming services have demonstrated the critical importance of maintaining high availability in cloud computing infrastructures. One of the methods used to identify the trends of occurrences of failures in computational systems, occurs through the application of strategies of sensitivity analysis. This paper uses hierarchical modeling and different sensitivity analysis techniques to determine the parameters that cause the greatest impact on the availability of a Video on Demand. The results show that distinct approaches provide similar results regarding the sensitivity ranking, with specific exceptions. A combined evaluation indicates that system availability may be improved effectively by focusing on a reduced set of factors that produce large variation on the measure of interest.
Evaluation of a Cloud Computing Environment by different Strategies of Sensitivity Analysis