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    Self-adaptive energy-efficent applications: The HADAS developing approach

    Autor: 
    Horcas, Jose Miguel
    ;
    Pinto, Mónica
    ;
    Fuentes, Lidia
    ;
    Gámez, Nádia (1)
    Fecha: 
    2017
    Palabra clave: 
    aspect-oriented software development; dynamic software product lines; energy-efficient applications; HADAS; self-adaptation; Scopus(2)
    Tipo de Ítem: 
    conferenceObject
    URI: 
    https://reunir.unir.net/handle/123456789/10482
    DOI: 
    https://doi.org/10.1109/DASC-PICom-DataCom-CyberSciTec.2017.140
    Dirección web: 
    https://ieeexplore.ieee.org/document/8328484/authors#authors
    Open Access
    Resumen:
    Software systems have a strong impact on the energy consumption of the hardware they use. For this reason, software developers should be more aware of the energy consumed by their systems. Moreover, software systems should be developed to be able to adapt their behavior to minimize the energy consumed during their execution. This paper illustrates how to address the problem of developing self-adaptive energy-efficient applications using the HADAS approach. HADAS makes use of advanced software engineering methods, such as Dynamic Software Product Lines and Aspect-Oriented Software Development. The main steps of the HADAS approach, both during the design of the application and also at runtime are illustrated by applying them to a running case study.
    Descripción: 
    Ponencia en la conferencia "Proceedings - 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017 Volume 2018-January, 29 March 2018, Pages 828-835 15th IEEE International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017; Orlando; United States; 6 November 2017 through 11 November 2017"
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