Person:
Núñez Covarrubias, Alberto

First Name

Alberto

Last Name

Núñez Covarrubias

URI

https://hdl.handle.net/20.500.14352/78602

Affiliation

Universidad Complutense de Madrid

Faculty / Institute

Informática

Department

Sistemas Informáticos y Computación

Area

Lenguajes y Sistemas Informáticos

Identifiers

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Search Results

Now showing 1 - 10 of 19

Profiling SLAs for cloud system infrastructures and user interactions
(PeerJ Computer Science, 2021) Bernal, Adrián; Valero, Valentín; Cambronero, M. Emilia; Núñez Covarrubias, Alberto; Cerro Cañizares, Pablo
Cloud computing has emerged as a cutting-edge technology which is widely used by both private and public institutions, since it eliminates the capital expense of buying, maintaining, and setting up both hardware and software. Clients pay for the services they use, under the so-called Service Level Agreements (SLAs), which are the contracts that establish the terms and costs of the services. In this paper, we propose the CloudCost UML profile, which allows the modeling of cloud architectures and the users’ behavior when they interact with the cloud to request resources. We then investigate how to increase the profits of cloud infrastructures by using price schemes. For this purpose, we distinguish between two types of users in the SLAs: regular and high-priority users. Regular users do not require a continuous service, so they can wait to be attended to. In contrast, high-priority users require a constant and immediate service, so they pay a greater price for their services. In addition, a computer-aided design tool, called MSCC (Modeling SLAs Cost Cloud), has been implemented to support the CloudCost profile, which enables the creation of specific cloud scenarios, as well as their edition and validation. Finally, we present a complete case study to illustrate the applicability of the CloudCost profile, thus making it possible to draw conclusions about how to increase the profits of the cloud infrastructures studied by adjusting the different cloud parameters and the resource configuration.
Project number: 55
Análisis de rendimiento de aplicaciones MPI en clusters de Raspberries Pi3
(2020) Núñez Covarrubias, Alberto; Pickin, Simon James; Lavín Puente, Víctor; Llana Díaz, Luis Fernando; Bartolomé Sandoval, Ana Isabel; Cerro Cañizares, Pablo; Cambronero Piqueras, Emilia; Ricaldi Esquivel, Javier Antonio; Gómez-Zamalloa Gil, Miguel
La asignatura Programación de Sistemas Distribuidos (PSD) dedica una parte del temario a las aplicaciones de alto rendimiento y, en particular, a las aplicaciones desarrolladas con MPI. En resumen, estas aplicaciones despliegan en las máquinas físicas del sistema distribuido una serie de procesos, los cuales deben explotar -de la forma más eficiente posible- los recursos compartidos del sistema para incrementar su rendimiento. El objetivo principal de este proyecto consiste en analizar el rendimiento de clusters de bajo presupuesto, concretamente, de sistemas formados por placas Raspberry Pi3.
MT-EA4Cloud: A Methodology For testing and optimising energy-aware cloud systems
(Journal of Systems and Software, 2020) Cañizares, Pablo C.; Núñez Covarrubias, Alberto; Lara, Juan de; Llana Díaz, Luis Fernando
Currently, using conventional techniques for checking and optimising the energy consumption in cloud systems is unpractical, due to the massive computational resources required. An appropriate test suite focusing on the parts of the cloud to be tested must be efficiently synthesised and executed, while the correctness of the test results must be checked. Additionally, alternative cloud configurations that optimise the energetic consumption of the cloud must be generated and analysed accordingly, which is challenging. To solve these issues we present MT-EA4Cloud, a formal approach to check the correctness – from an energy-aware point of view – of cloud systems and optimise their energy consumption. To make the checking of energy consumption practical, MT-EA4Cloud combines metamorphic testing, evolutionary algorithms and simulation. Metamorphic testing allows to formally model the underlying cloud infrastructure in the form of metamorphic relations. We use metamorphic testing to alleviate both the reliable test set problem, generating appropriate test suites focused on the features reflected in the metamorphic relations, and the oracle problem, using the metamorphic relations to check the generated results automatically. MT-EA4Cloud uses evolutionary algorithms to efficiently guide the search for optimising the energetic consumption of cloud systems, which can be calculated using different cloud simulators.
Project number: 17
Diseño y despliegue de un clúster de placas Raspberry Pi3 para la ejecución de las prácticas de la asignatura PSD
(2018) Núñez Covarrubias, Alberto; Llana Díaz, Luis; Lavín Puente, Víctor; James Pickin, Simon; Bartolomé Sandoval, Ana; Cerro Cañizares, Pablo; Cambronero Piqueras, Emilia; Romero Martínez, Miguel; Quiñones Sánzhez, Daniel; Mañoso Hierro, Carolina; Pérez de Madrid y Pablo, Ángel; Romero Hortelano, Miguel
Este proyecto tiene como objetivo principal facilitar el desarrollo de las prácticas de la asignatura Programación de Sistemas Distribuidos (PSD), impartida en el grado en Ingeniería de Computadores de la FDI. Esta propuesta surge como continuación del proyecto de innovación docente concedido en el curso 16/17, en el cual se utilizó la herramienta de simulación SIMCAN para estudiar y analizar distintos tipos de sistemas distribuidos en las prácticas de la asignatura PSD.
Chaos as a Software Product Line - A platform for improving open hybrid-cloud systems resiliency
(Software - Practice and Experience, 2022) Camacho, Carlos; Cerro Cañizares, Pablo; Llana Díaz, Luis Fernando; Núñez Covarrubias, Alberto
Nowadays, cloud-native software architectures have a significant relevance due to the speed and agility they provide. These properties lead relevant organizations in different industries, like video streaming (Netflix), car-sharing (Uber, Cabify), banking (BBVA, HSBC), and governmental agencies (NASA, FBI, CERN, ESA) to heavily rely on cloud-native software to run their business-critical applications. Additionally, including fault injection actions in the production infrastructure allows companies to have consistent environments, to improve applications dependability against unexpected failures, to provide better user experience, and to improve the overall system quality. Thus, cloud computing technologies allow development teams to rapidly create complex systems and to continuously deploy them, at a global scale. This work describes Pystol, a novel fault injection platform—represented as a Software Product Line—to analyze the effects caused by a wide spectrum of adverse conditions. Pystol is designed to be executed on top of cloud-native environments, either in private or public clouds. The proposed architecture shows a way for representing feature models based on Unified Model Language (in short, UML) component diagrams. Furthermore, we present a thorough empirical study carried out in real-world environments, providing promising results.
SIMCAN: A simulator to improve the learning of distributed and high-performance computing systems in engineering degrees
(Computer Applications in Engineering Education, 2019) Núñez Covarrubias, Alberto; Mañoso, Carolina; de Madrid, Ángel Pérez; Pickin, Simón James
Distributed systems programming (DSP) is an important subject in the Computer Engineering undergraduate degree. The use of a version of the SIMCAM simulator adapted to the educational context enabled our DSP students to exercise important facets of DSP that are otherwise difficult or impossible to incorporate in student activities. Analyzing and quantifying the assumed benefits of this educational intervention on student learning enables us to better adapt such interventions to student needs. To investigate the impact on student learning of this novel use of a simulator we analyze both the course-assessment results and the constructors of the technology acceptance model, the latter via an initial survey of student perceptions carried out at the beginning of the course and another carried out after completing the simulator-based assignment. We observe, in particular, an improvement in the overall grades between the target year and those of the year previous to the simulator introduction. Moreover, other statistical findings are also of interest.
Evaluating cloud interactions with costs and SLAs
(The Journal of Supercomputing, 2021) Bernal, Adrián; Cambronero, M. Emilia; Núñez Covarrubias, Alberto; Cerro Cañizares, Pablo; Valero, Valentín
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.
Automated engineering of domain-specific metamorphic testing environments
(Information and Software Technology, 2023) Gómez-Abajo, Pablo; Cerro Cañizares, Pablo; Núñez Covarrubias, Alberto; Guerra, Esther; de Lara, Juan
Context: Testing is essential to improve the correctness of software systems. Metamorphic testing (MT) is an approach especially suited when the system under test lacks oracles, or they are expensive to compute. However, building an MT environment for a particular domain (e.g., cloud simulation, model transformation, machine learning) requires substantial effort. Objective: Our goal is to facilitate the construction of MT environments for specific domains. Method: We propose a model-driven engineering approach to automate the construction of MT environments. Starting from a meta-model capturing the domain concepts, and a description of the domain execution environment, our approach produces an MT environment featuring comprehensive support for the MT process. This includes the definition of domain-specific metamorphic relations, their evaluation, detailed reporting of the testing results, and the automated search-based generation of follow-up test cases. Results: Our method is supported by an extensible platform for Eclipse, called Gotten. We demonstrate its effectiveness by creating an MT environment for simulation-based testing of data centres and comparing with existing tools; its suitability to conduct MT processes by replicating previous experiments; and its generality by building another MT environment for video streaming APIs. Conclusion: Gotten is the first platform targeted at reducing the development effort of domain-specific MT environments. The environments created with Gotten facilitate the specification of metamorphic relations, their evaluation, and the generation of new test cases.
MT-EA4Cloud: A Methodology For testing and optimising energy-aware cloud systems
(Journal of Systems and Software, 2020) Cerro Cañizares, Pablo; Núñez Covarrubias, Alberto; de Lara, Juan; Llana Díaz, Luis Fernando
Currently, using conventional techniques for checking and optimising the energy consumption in cloud systems is unpractical, due to the massive computational resources required. An appropriate test suite focusing on the parts of the cloud to be tested must be efficiently synthesised and executed, while the correctness of the test results must be checked. Additionally, alternative cloud configurations that optimise the energetic consumption of the cloud must be generated and analysed accordingly, which is challenging. To solve these issues we present MT-EA4Cloud, a formal approach to check the correctness – from an energy-aware point of view – of cloud systems and optimise their energy consumption. To make the checking of energy consumption practical, MT-EA4Cloud combines metamorphic testing, evolutionary algorithms and simulation. Metamorphic testing allows to formally model the underlying cloud infrastructure in the form of metamorphic relations. We use metamorphic testing to alleviate both the reliable test set problem, generating appropriate test suites focused on the features reflected in the metamorphic relations, and the oracle problem, using the metamorphic relations to check the generated results automatically. MT-EA4Cloud uses evolutionary algorithms to efficiently guide the search for optimising the energetic consumption of cloud systems, which can be calculated using different cloud simulators.
CloudExpert: An intelligent system for selecting cloud system simulators
(Expert Systems with Applications, 2021) Núñez Covarrubias, Alberto; Cerro Cañizares, Pablo; de Lara, Juan
During the last decade, the research community has developed different simulation tools to model and study cloud systems. However, current cloud simulators focus on specific features that typically do not fully cover all aspects of the cloud infrastructure. The ever-growing number of existing simulators increases the difficulty to properly choose the most appropriate one. Moreover, in certain situations, these simulators must be combined to analyze the features required by the user, which leads to investing a considerable time and effort for their selection. In this paper, we propose CloudExpert, an intelligent system based on metamorphic testing that selects the most appropriate simulator covering the features of interest for the user. In contrast to our previous work, where metamorphic testing is applied to improve models representing a cloud, in this work we analyse the underlying features of several well-known cloud simulators to generate metamorphic rules, which are applied to represent the properties of the simulator. To show the applicability of CloudExpert, we conducted an empirical study where the adequacy of six well-known cloud simulators was analyzed. In this experiment, CloudExpert recommended the most appropriate simulator for eight scenarios involving different aspects of the cloud (energy, storage, network, memory, CPU) and simulator performance; and could also identify strengths and weaknesses of these simulators. Then, we further validated CloudExpert in two different ways. Firstly, the effectiveness of CloudExpert was measured using different faulty cloud simulators. Secondly, we designed a questionnaire based on the results provided by CloudExpert for some of the scenarios of the first experiment. The questionnaire was answered by eight experts in cloud simulation, confirming the usefulness of the tool.