Energy efficient assignment and deployment of tasks in structurally variable infrastructures

The importance of cyber-physical systems is growing very fast, being part of the Internet of Things vision. These devices generate data that could collapse the network and can not be assumed by the cloud. New technologies like Mobile Cloud Computing and Mobile Edge Computing are taking importance as solution for this issue. The idea is offloading some tasks to devices situated closer to the user device, reducing network congestion and improving applications performance (e.g., in terms of latency and energy). However, the variability of the target devices’ features and processing tasks’ requirements is very diverse, being difficult to decide which device is more adequate to deploy and run such processing tasks. Once decided, task offloading used to be done manually. Then, it is necessary a method to automatize the task assignation and deployment process. In this thesis we propose to model the structural variability of the deployment infrastructure and applications using feature models, on the basis of a SPL engineering process. Combining SPL methodology with Edge Computing, the deployment of applications is addressed as the derivation of a product. The data of the valid configurations is used by a task assignment framework, which determines the optimal tasks offloading solution in different network devices, and the resources of them that should be assigned to each task/user. Our solution provides the most energy and latency efficient deployment solution, accomplishing the QoS requirements of the application in the process.Plan Propio de Investigación de la UMA Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Supporting IoT applications deployment on edge-based infrastructures using multi-layer feature models

Edge Computing proposes to use the nearby devices in the frontier/Edge of the access network for deploying application tasks of IoT-based systems. However, the functionality of such cyber–physical systems, which is usually distributed in several devices and computers, imposes specific requirements on the infrastructure to run properly. The evolution of an application to meet new user requirements and the high diversity of hardware and software technologies in the IoT/Edge/Cloud can complicate the deployment of continuously evolving applications. The aim of our approach is to apply Multi Layer Feature Models, which capture the variability of applications and the software and hardware infrastructure, to support the deployment in edge-based environments of cyber–physical applications. With this multi-layered approach is possible to support the evolution of application and infrastructure independently. Considering that IoT/Edge/Cloud infrastructures are usually shared by many applications, the deployment process has to assure that there will be enough resources for all of them, informing developers about the feasible alternatives. We provide four modules so that the developer can calculate what is the configuration of minimal set of devices supporting application requirements of the evolved application. In addition, the developer can find what is the application configuration that can be hosted in the current infrastructure. The successive solutions of continuous deployment generated by our approach pursue the reduction of the system energy footprint and/or execution latency.This work is supported by the European Union’s H2020 research and innovation programme under grant agreement DAEMON 101017109 and by the projects co-financed by FEDER funds, Spain LEIA UMA18-FEDERJA-15, MEDEA RTI2018-099213-B-I00 (MCI/AEI) and RHEA P18-FR-1081. Funding for open access charge: Universidad de Málaga/CBUA

Mecanismos de reconfiguración eco-eficiente de código en aplicaciones móviles Android

Los dispositivos móviles ofrecen cada vez mayores prestaciones a costa de un mayor consumo energético. La energía consumida por un móvil no sólo depende de las aplicaciones en sí, sino también de las interacciones del usuario con la aplicación. Si un recurso no está siendo utilizado por la aplicación, no debería estar consumiendo energía. En este artículo se presenta un modelo de adaptación de aplicaciones móviles al contexto del usuario con el objetivo de reducir el consumo energético de las aplicaciones. Se desarrollan y evalúan cuatro implementaciones diferentes de la propuesta en busca del mecanismo de reconfiguración más eficiente energéticamente

Optimal Assignment of Augmented Reality Tasks for Edge-Based Variable Infrastructures

In the last few years, the number of devices connected to the Internet has increased considerably; so has the data interchanged between these devices and the Cloud, as well as energy consumption and the risk of network congestion. The problem can be alleviated by reducing communication between Internet-of-Things devices and the Cloud. Recent paradigms, such as Edge Computing and Fog Computing, propose to move data processing tasks from the Cloud to nearby devices to where data is produced or consumed. One of the main challenges of these paradigms is to cope with the heterogeneity of the infrastructures where tasks can be offloaded. This paper presents a solution for the optimal allocation of computational tasks to edge devices, with the aim of minimizing the energy consumption of the overall application. The heterogeneity is represented and managed by using Feature Models, widely employed in Software Product Lines. Given the application and infrastructure configurations, our Optimal Tasks Assignment Framework generates the optimal task allocation and resources assignment. The resultant deployment represents the most energy efficient configuration at load-time, without compromising the user experience. The scalability and energy saving of the approach are evaluated in the domain of augmented reality applicationsHADAS TIN2015-64841-R (co-funded by FEDER funds), TASOVA MCIU-AEI TIN2017-90644-REDT, MEDEA RTI2018-099213-B-I00 (co-funded by FEDER funds) LEIA UMA18-FEDERJA-157 (co-funded by FEDER funds) Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Interventional cardiology : resolution of congenital heart diseases in small animals

PòsterFebre

Energy efficient adaptation engines for android applications

Context The energy consumption of mobile devices is increasing due to the improvement in their components (e.g., better processors, larger screens). Although the hardware consumes the energy, the software is responsible for managing hardware resources such as the camera software and its functionality, and therefore, affects the energy consumption. Energy consumption not only depends on the installed code, but also on the execution context (environment, devices status) and how the user interacts with the application. Objective In order to reduce the energy consumption based on user behavior, it is necessary to dynamically adapt the application. However, the adaptation mechanism also consumes a certain amount of energy in itself, which may lead to an important increase in the energy expenditure of the application in comparison with the benefits of the adaptation. Therefore, this footprint must be measured and compared with the benefit obtained. Method In this paper, we (1) determine the benefits, in terms of energy consumption, of dynamically adapting mobile applications, based on user behavior; and (2) advocate the most energy-efficient adaptation mechanism. We provide four different implementations of a proposed adaptation model and measure their energy consumption. Results The proposed adaptation engines do not increase the energy consumption when compared to the benefits of the adaptation, which can reduce the energy consumption by up to 20%. Conclusion The adaptation engines proposed in this paper can decrease the energy consumption of the mobile devices based on user behavior. The overhead introduced by the adaptation engines is negligible in comparison with the benefits obtained by the adaptation.Junta de Andalucía MAGIC P12-TIC1814Ministerio de Economía y Competitividad TIN2015-64841-RMinisterio de Ciencia, Innovación y Universidades TIN2017-90644-REDTMinisterio de Ciencia, Innovación y Universidades RTI2018-099213-B-I00Universidad de Málaga LEIA UMA18-FEDERJA-15

El ácido úrico se asocia con características de un síndrome de resistencia insulínica en los niños obesos en etapas perdurables

Elevated plasma uric acid levels are associated with obesity and could be an expression of insulin-resistant state. The aim of the present study was to evaluate plasma uric acid in obese and normal-weight children exclusively at prepubertal stage and its relationship with anthropometric measurements, intake, and features of the insulin resistance syndrome. A study was performed in 34 obese and 20 normal- weight prepubertal children. Nutrient intake was determined using a 72 h recall questionnaire and a consumption food frequency questionnaire. Anthropometric parameters and fasting plasma lipids, glucose, insulin, leptin, adiponectin, tumour necrosis factor (TNF-α) and uric acid were measured. Multiple regression analysis was used to identify association of anthropometric parameters, nutrient intake and insulin resistance syndrome variables (arterial blood pressure, plasma glucose, insulin, homeostasis model assessment of insulin resistance index- HOMA- triacylglycerols and, HDL-cholesterol) with uric acid. Plasma uric concentration was significantly higher in the obese group than in the control group and when adjusted by sex, age and BMI was positively associated with tricipital skinfold and insulin resistance, and negatively with adiponectin. In multiple regression analysis, BMI, HDL-cholesterol and adiponectin were independent predictors of plasma uric acid. In conclusion, elevated levels of uric acid in obese children, compared with lean subjects, at the prepubertal period, seems to be an early metabolic alteration that is associated with other features of insulin resistance syndrome.Los niveles elevados de ácido úrico plasmáticos se asocian a la obesidad y pueden ser la expresión de un estado de resistencia insulínica. El objetivo de este estudio ha sido evaluar la concentración plasmática de ácido úrico en niños obesos y normales, exclusivamente en edad prepuberal, y determinar su relación con las medidas antropométricas, la ingesta dietética y los parámetros asociados al síndrome de resistencia insulínica. El estudio se llevó a cabo en 34 niños obesos y 20 controles en edad prepuberal a los cuales se les estimó su ingesta dietética mediante el registro de un cuestionario de ingesta de alimentos de 72 h y un cuestionario de frecuencia de consumo de alimentos y se determinaron, además de los parámetros antropométricos, la glucosa, la insulina, la leptina, la adiponectina y el factor de necrosis tumoral alfa (TNF-α) plasmáticos. Se realizó un análisis de regresión múltiple para identificar la asociación entre los niveles de ácido úrico y los parámetros antropométricos, la ingesta de nutrientes y las variables clásicas relacionadas con el síndrome de resistencia insulínica (hipertensión, glucosa, insulina, índice de resistencia insulínica HOMA, triglicéridos y HDL-colesterol plasmáticos), así como con leptina, adiponectina y TNF-α. La concentración plasmática de ácido úrico fue significativamente más elevada en los niños obesos que en los controles y, cuando se ajustó por sexo, edad e índice de masa corporal, los niveles de ácido úrico se asociaron con el pliegue tricipital y la resistencia inulínica, y negativamente con la adiponectina. En el análisis de regresión múltiple, el índice de masa corporal, el HDL-colesterol y la adiponectina fueron predictores independientes del ácido úrico plasmático. En conclusión, los niveles elevados de ácido úrico en niños obesos en edad prepuberal, comparado con los de los niños normales, representan una alteración metabólica temprana asociada con la resistencia insulínica.This work was supported by the Spanish Ministry of Health and Consumer Affairs, the Spanish National Program for Scientific Research, Development, and Technological Innovation (I+D+I), and the Instituto de Salud Carlos III (Spanish National Health Research Institute), FEDER co-financed Project No. PI 051968. Mercedes Gil-Campos was a research scientist appointed on a training contract funded by the Carlos III Health Research Institute

Energy-efficient Deployment of IoT Applications in Edge-based Infrastructures: A Software Product Line Approach

In order to lower latency and reduce energy consumption, Edge Computing proposes offloading some computation intensive tasks usually performed in the Cloud onto nearby devices in the frontier/Edge of the access networks. However, current task offloading approaches are often quite simple. They neither consider the high diversity of hardware and software technologies present in edge network devices, nor take into account that some tasks may require some specific software and hardware infrastructure to be executed. This paper proposes a task offloading process that leans on Software Product Line technologies, which are a very good option to model the variability of software and hardware present in edge environments. Firstly, our approach automates the separation of application tasks, considering the data and operation needs and restrictions among them, and identifying the hardware and software resources required by each task. Secondly, our approach models and manages separately the infrastructure available for task offloading, as a set of nodes that provide certain hardware and software resources. This separation allows to reason about alternative offloading of tasks with different hardware and software resource requirements, in heterogeneous nodes and minimizing energy consumption. In addition, the offloading process considers alternative implementations of tasks to choose the one that best fits the hardware and software characteristics of available edge network infrastructure. The experimental results shows that our approach reduces the energy consumption in the user node by approximately 41%–62%, and the energy consumption of the devices involved in a task offloading solution by 34-48%Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Análisis teórico-cuantitativo de la constitución formal de los hipocorísticos en español peninsular

El proceso de formación de hipocorísticos (Fran, Isa) es difícil de sistematizar debido a los cambios formales y prosódicos que experimentan respecto a sus bases. Estos se clasifican en dos grupos en función del mantenimiento de la sílaba inicial y su mayor fidelidad formal a la base (clase A) o del mantenimiento de la sílaba tónica y la mayor presencia de cambios formales para obtener sílabas CV.CV (clase B). Nuestro análisis estadístico de una muestra actualizada de 208 hipocorísticos muestra que la distribución de los nombres en ambas clases no es aleatoria, siendo el número de sílabas de la base un factor determinante. Se observan, además, diferencias significativas en función del género, siendo los hipocorísticos femeninos generalmente más conservadores que los masculinos. También la aparición de sonidos palatales es mayor en estos últimos, pese a que los estudios previos vinculaban esta estrategia a la formación de hipocorísticos femeninos

El juego como herramienta para regular las emociones y mejorar el rendimiento académico de alumnos de sexto de Educación Primaria

Esta investigación tiene la finalidad de conocer cómo las emociones surgidas por la participación de los estudiantes en juegos pueden influir en su rendimiento académico. Según la interacción motriz realizada en la clase de Educación física se estudia como las asignaturas de Lengua castellana y Matemáticas van a ser influenciadas por las emociones emitidas en los juegos.<br /