| dc.description.abstract | Due to constant technological advances, there are new trends to provide a service base for the new era of information technology. Thus, there are new paradigms for distributed systems, for example, Cloud Computing, which has as basic idea of the provision of computational resources on demand via the Internet, thus allowing their use anywhere and for many different types of applications. Among the main features of cloud computing, there is elasticity, service provisioning and billing based on the effective use of resources. In order to make these features in practice possible, it is essential that the infrastructure to have a monitoring system. In this context, this work presents the BSPMon, a monitoring system of predictive features for parallel applications in Cloud Computing. In order to have fine control over computing resources, the BSPMon collect performance metrics in three levels of infrastructure: physical machine, virtual machine and application, making thus a multilevel hierarchical resource monitoring. With such performance metrics, the BSPMon shall make predictions about the demands, to obtain better results for decision making in migration scenarios, prediction, control over the SLA, provisioning and consolidation of resources. The proposed system will operate in the middleware level, transparently to the application. From the evaluations obtained in the prediction, the results indicate low intrusiveness in infrastructure, energy efficiency and predictions accuracy rate above 90 %. | en |
