HADAS: tool for analysis and development of sustainable applications

Durante esta Conferencia Internacional, representantes del Gobierno, autoridades locales, instituciones públicas y privadas, vicerrectores de Internacionalización y talento nacional e internacional crearon un ecosistema para fomentar las colaboraciones nacionales e internacionales, así como la presentación de nuevas ideas para resolver retos que afectan a la sociedad. Se trata de un foro único, donde se presentaron trabajos científicos y se otorgaron premios con el fin de fomentar el rigor y la excelencia científica.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Run-time Support to Manage Architectural Variability Speci ed with CVL

The execution context in which pervasive systems or mobile computing run changes continuously. Hence, applications for these systems should be adapted at run-time according to the current context. In order to implement a context-aware dynamic reconfiguration service, most approaches usually require to model at design-time both the list of all possible configurations and the plans to switch among them. In this paper we present an alternative approach for the automatic run-time generation of application configurations and the reconfiguration plans. The generated configurations are optimal regarding di erent criteria, such as functionality or resource consumption (e.g. battery or memory). This is achieved by: (1) modelling architectural variability at design-time using Common Variability Language (CVL), and (2) using a genetic algorithm that finds at run-time nearly-optimal configurations using the information provided by the variability model. We also specify a case study and we use it to evaluate our approach, showing that it is efficient and suitable for devices with scarce resources.Campus de Excelencia Internacional Andalucia Tech y proyectos de investigación TIN2008-01942, P09-TIC-5231 and INTER-TRUST FP7-317731

An empirical study of power consumption of Web-based communications in mobile phones

Currently, mobile devices are the most popular pervasive computing device, and they are becoming the primer way for Web access. Energy is a critical resource in such pervasive computing devices, being network communication one of the primary energy consuming operations in mobile apps. Indeed, web-based communication is the most used, but also energy demanding. So, mobile web developers should be aware of how much energy consumes the different web-based communication alternatives. The goal of this paper is to measure and compare the energy consumption of three asynchronous Web-based methods in mobile devices. Our experiments consider three different Web applications models that allow a web server to push data to a browser: Polling, Long Polling and WebSockets. The obtained results are analyzed to get more accurate understanding of the impact in energy consumption of a mobile browser for each of these three methods. The utility of these experiments is to show developers what are the factors that influence the energy consumption when different web-based asynchronous communication is used. With this information mobile web developers could reduce the power consumption of web applications on mobile devices, by selecting the most appropriate method for asynchronous server communication.MUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Model Driven Evolution of an Agent-Based Home Energy Management System

Advanced smart home appliances and new models of energy tariffs imposed by energy providers pose new challenges in the automation of home energy management. Users need some assistant tool that helps them to make complex decisions with different goals, depending on the current situation. Multi-agent systems have proved to be a suitable technology to develop self-management systems, able to take the most adequate decision under different context-dependent situations, like the home energy management. The heterogeneity of home appliances and also the changes in the energy policies of providers introduce the necessity of explicitly modeling this variability. But, multi-agent systems lack of mechanisms to effectively deal with the different degrees of variability required by these kinds of systems. Software Product Line technologies, including variability models, has been successfully applied to different domains to explicitly model any kind of variability. We have defined a software product line development process that performs a model driven generation of agents embedded in heterogeneous smart objects with different degrees of self-management. However, once deployed, the home energy assistant system has to be able to evolve to self-adapt its decision making or devices to new requirements. So, in this paper we propose a model driven mechanism to automatically manage the evolution of multi-agent systems distributed among several devices.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

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

vEXgine: extendiendo el motor de ejecución de CVL

El Lenguaje CVL (Common Variability Language) carece de una herramienta flexible que permita poner en práctica las necesidades industriales del modelado de la variabilidad en Líneas de Producto Software. Las herramientas existentes que proporcionan soporte para CVL son prototipos incompletos, o se centran principalmente en la especificación de la variabilidad, sin llegar a resolverla sobre modelos reales. Además, no existe una API que permita la interacción directa con el motor CVL para extenderlo o usarlo en una aplicación independiente. Este artículo presenta vEXgine, una implementación adaptable y extensible del motor de ejecución de la variabilidad de CVL.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Proyectos MAGIC P12-TIC1814 y HADAS TIN2015-64841-

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

Run-time Adaptation of Mobile Applications using Genetic Algorithms

Mobile applications run in environments where the context is continuously changing. Therefore, it is necessary to provide support for the run-time adaptation of these applications. This support is usually achieved by middleware platforms that offer a context-aware dynamic reconfiguration service. However, the main shortcoming of existing approaches is that both the list of possible configurations and the plans to adapt the application to a new configuration are usually specified at design-time. In this paper we present an approach that allows the automatic generation at run-time of application configurations and of reconfiguration plans. Moreover, the generated configurations are optimal regarding the provided functionality and, more importantly, without exceeding the available resources (e.g. battery). This is performed by: (1) having the information about the application variability available at runtime using feature models, and (2) using an genetic algorithm that allows generating an optimal configuration at runtime. We have specified a case study and evaluated our approach, and the results show that it is efficient enough as to be used on mobile devices without introducing an excessive overhead.Campus de Excelencia Andalucía Tech y Proyectos de investigación TIN2008-01942, P09-TIC-5231 y INTER-TRUST FP7-317731

A modular metamodel and refactoring rules to achieve software product line interoperability.

Emergent application domains, such as cyber–physical systems, edge computing or industry 4.0. present a high variability in software and hardware infrastructures. However, no single variability modeling language supports all language extensions required by these application domains (i.e., attributes, group cardinalities, clonables, complex constraints). This limitation is an open challenge that should be tackled by the software engineering field, and specifically by the software product line (SPL) community. A possible solution could be to define a completely new language, but this has a high cost in terms of adoption time and development of new tools. A more viable alternative is the definition of refactoring and specialization rules that allow interoperability between existing variability languages. However, with this approach, these rules cannot be reused across languages because each language uses a different set of modeling concepts and a different concrete syntax. Our approach relies on a modular and extensible metamodel that defines a common abstract syntax for existing variability modeling extensions. We map existing feature modeling languages in the SPL community to our common abstract syntax. Using our abstract syntax, we define refactoring rules at the language construct level that help to achieve interoperability between variability modeling languages.Work supported by the projects MEDEA RTI2018-099213-B-I00, IRIS PID2021-122812OB-I00 (co-financed by FEDER funds), Rhea P18-FR-1081 (MCI/AEI/FEDER, UE), LEIA UMA18-FEDERIA-157, and DAEMON H2020-101017109. // Funding for open access: Universidad de Málaga / CBUA

Analysis and optimisation of SPL products using goal models.

https://conf.researchr.org/details/RE-2023/RE-2023-Research-Papers/10/Analysis-and-optimisation-of-SPL-products-using-goal-modelsThe Internet of Things is one of the core drivers of variability modelling and requires explicit mechanisms to manage it. A key technology for addressing this variability is product line engineering. This approach uses a reference architecture to establish a well-designed set of assets that fit together, the Software Product Line (SPL). One of the limitations of variability models is they do not provide information about the quality of new products or how they achieve stakeholder requirements. Several approaches tackle this issue by integrating variability models with goal models. The main challenge is conciliating the different variability perspectives to make the joint use of both models possible without the loss of information or alterations to the models’ semantics. In this work, we present a framework for analysing and optimising SPL products considering stakeholders’ requirements that respects the semantics of both models. The framework is based on Integer Linear Programming (ILP), a field of mathematical programming. Variability and goal models are formalised as a set of linear constraints and are linked using mapping functions. As a proof of concept, we present a tool that takes both models and mapping functions to generate an ILP problem that can be solved using Matlab.This work is supported by the projects IRIS PID2021-12281 2OB-I00 (co-financed by FEDER funds) and by DISCO B1- 201212 funded by Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech