Abstract In this paper, we investigate how to improve the profits in cloud infrastructures by using price schemes and analyzing the user interactions with the cloud provider. For this purpose, we consider two different types of client behavior, namely regular and high-priority users. Regular users do not require a continuous service, and they can wait to be attended to. In contrast, high-priority users require a continuous service, e.g., a 24/7 service, and usually need an immediate answer to any request. A complete framework has been implemented, which includes a UML profile that allows us to define specific cloud scenarios and the automatic transformations to produce the code for the cloud simulations in the Simcan2Cloud simulator. The engine of Simcan2Cloud has also been modified by adding specific SLAs and price schemes. Finally, we present a thorough experimental study to analyze the performance results obtained from the simulations, thus making it possible to draw conclusions about how to improve the cloud profit for the cloud studied by adjusting the different parameters and resource configuration.

In this paper, we model cloud systems and the user interactions with the cloud provider using the UML2Cloud profile.In general, users request virtual machines according to their needs, but they can also subscribe to the cloud provider and wait to be notified when the requested resources are not available.In this case, users indicate a maximum subscription time, so once this time elapses without being notified, users leave the system unattended.In this paper, then, we present an exhaustive research study to measure how the user subscription times affect the overall system responsiveness.In this study, three different cloud configurations are analyzed.Each cloud processes several workloads, which are generated using two distribution functions for the user arrivals, namely a normal and a cyclic normal distribution.The purpose of this study is to find out the inflection point for the waiting time of the users, from which the cloud responsiveness and its performance do not improve.The obtained information is therefore useful for the cloud provider to improve the configuration of the cloud.

Cloud providers face the challenge of managing large amounts of heterogeneous resources in real time. It is usually very costly to conduct experiments with real cloud systems. Therefore, tools to analyze and evaluate cloud scenarios and experimental studies are very useful for them. In this paper, we model cloud systems and the user interactions with the cloud provider using the UML2Cloud profile. In general, users request virtual machines according to their needs, but they can also subscribe to the cloud provider and wait to be notified when the requested resources are not available. In this case, users indicate a maximum subscription time, so once this time elapses without being notified, users leave the system unattended. Thus, we present an exhaustive experimental study to measure how the user subscription times affect the overall system responsiveness. To this end, four different cloud configurations are analyzed, and the workloads for these studies are produced by using three distribution functions for the user arrivals, namely, a uniform, a normal, and a cyclic normal distribution. Furthermore, we also analyze the cloud performance with a workload obtained from a real trace. The purpose of this study is to find out the inflection point for the waiting time of the users, from which the cloud responsiveness and its performance do not improve. The obtained information is, therefore, useful for the cloud provider to improve the configuration of the cloud.