Browsing by Author "Insfran, Emilio"

Now showing 1 - 3 of 3

Automatización del proceso de despliegue de servicios en la nube
(Universidad de Cuenca, 2016-11-16) Zuñiga-Prieto, Miguel; Solano-Quinde, Lizandro; Insfran, Emilio; Cabrera, Yessenia
The lack of standardization of the access methods and the management of resources in cloud environments hinders both, the portability of services between different cloud environments, and the agile deployment of services. In this context, it is important to reduce the deployment time in order to reduce the economic cost to organizations. The manuscript presents an approach for automating the deployment process of cloud services, by proposing a language that specifies the resource needs in cloud environments, in support to the logic of cloud services. The information about requirements is used for generating resource provisioning scripts and service configurations, both, specific to the deployment platform. This approach is applied to a case study in the Windows Azure© platform, used as a deployment environment and the development of a deployment script based on the cloud resource specification.
Empirical evaluation of a method for monitoring cloud services based on models at runtime
(2021) Abrahao, Silvia; Cedillo Orellana, Irene Priscila; Insfran, Emilio; Vanderdonckt, Jean
Cloud computing is being adopted by commercial and governmental organizations driven by the need to reduce the operational cost of their information technology resources and search for a scalable and flexible way to provide and release their software services. In this computing model, the Quality of Services (QoS) is agreed between service providers and their customers through Service Level Agreements (SLA). There is thus a need for systematic approaches with which to assess the quality of cloud services and their compliance with the SLA. In previous work, we introduced a generic method for Monitoring cloud Services using models at RunTime (MoS@RT), which allows the monitoring requirements or the metric operationalizations of these requirements to be changed at runtime without the modification of the underlying infrastructure. In this paper, we present the design of a monitoring infrastructure that supports the proposed method with its instantiation to a specific platform and reports the results of an experiment carried out to evaluate the perceived efficacy of 58 undergraduate students when using the infrastructure to configure the monitoring of cloud services deployed on the Microsoft Azure platform. The results show that the participants perceived MoS@RT to be easy to use, useful, and they also expressed their intention to use the method in the future. Although further experiments must be carried out to strengthen these results, MoS@RT has proved to be a promising monitoring method for cloud services.
Monitoring cloud services through models at runtime: a case in an ambient assisted living environment
(2022) Insfran, Emilio; Abrahao Mara, Silvia; Cedillo Orellana, Irene Priscila
Ambient Assisted Living (AAL) has become an important domain that provides software systems and services to support and improve people’s daily quality of life. Yet, it has not achieved large market penetration. Existing works suggest that this is primarily due to not sufficiently addressing the quality requirements posed by healthcare organizations. In particular, there is a lack of comprehensive frameworks that allow the assessment of the quality of AAL systems. In previous work, we introduced a method for monitoring cloud services using models at runtime (MoS@RT), which allows the monitoring requirements or the metric operationalizations of these requirements to be changed at runtime without the modification of the underlying infrastructure. The method and its supporting infrastructure have been successfully applied in the monitoring of cloud services, but further evaluation in other domains is needed. In this paper, we report a case study on the use of MoS@RT to monitor cloud services in an AAL environment aimed at supporting the elderly’s well-being. The results suggest that relevant quality attributes of AAL systems can be adequately monitored using MoS@RT and that the report generated by the monitoring infrastructure is useful for service providers and customers to help them ensure that cloud services meet the required levels of quality.