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MT-EA4Cloud: A Methodology For testing and optimising energy-aware cloud systems

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  • معلومة اضافية
    • بيانات النشر:
      Elsevier
    • الموضوع:
      2020
    • Collection:
      Universidad Complutense de Madrid (UCM): E-Prints Complutense
    • نبذة مختصرة :
      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. ; Sección Deptal. de Sistemas Informáticos y Computación ; Fac. de Ciencias Matemáticas ; FALSE ; Ministerio de Economía y Competitividad (MINECO)/FEDER ; Comunidad de Madrid ; Universidad Complutense de Madrid/Banco de Santander ; pub
    • File Description:
      application/pdf
    • ISSN:
      01641212
    • Relation:
      DArDOS (TIN2015-65845-C3-1-R); FAME (RTI2018-093608-B-C31); MASSIVE (RTI2018-095255-B-I00); FORTE-CM (S2018/TCS-4314); CT17/17-CT18/17; https://doi.org/10.1016/j.jss.2020.110522; https://www.sciencedirect.com/science/article/pii/S0164121220300054; https://hdl.handle.net/20.500.14352/7730
    • الرقم المعرف:
      10.1016/j.jss.2020.110522
    • الدخول الالكتروني :
      https://hdl.handle.net/20.500.14352/7730
      https://doi.org/10.1016/j.jss.2020.110522
      https://www.sciencedirect.com/science/article/pii/S0164121220300054
    • Rights:
      open access
    • الرقم المعرف:
      edsbas.99DA69FE