Artículo
DISCERNER: Dynamic selection of resource manager in hyper-scale cloud-computing data centres
Autor/es | Fernández Cerero, Damián
Ortega Rodríguez, Francisco Javier Jakóbik, Agnieszka Fernández Montes González, Alejandro |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2021 |
Fecha de depósito | 2022-03-11 |
Publicado en |
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Premios | Premio Mensual Publicación Científica Destacada de la US. Escuela Técnica Superior de Ingeniería Informática |
Resumen | Data centres constitute the engine of the Internet, and run a major portion of large web and mobile
applications, content delivery and sharing platforms, and Cloud-computing business models. The high
performance of such ... Data centres constitute the engine of the Internet, and run a major portion of large web and mobile applications, content delivery and sharing platforms, and Cloud-computing business models. The high performance of such infrastructures is therefore critical for their correct functioning. This work focuses on the improvement of data-centre performance by dynamically switching the main data-centre governance software system: the resource manager. Instead of focusing on the development of new resource-managing models as soon as new workloads and patterns appear, we propose DISCERNER, a decision-theory model that can learn from numerous data-centre execution logs to determine which existing resource-managing model may optimise the overall performance for a given time period. Such a decision-theory system employs a classic machine-learning classifier to make real-time decisions based on past execution logs and on the current data-centre operational situation. A set of extensive and industry-guided experiments has been simulated by a validated data-centre simulation tool. The results obtained show that the values of key performance indicators may be improved by at least 20% in realistic scenarios. |
Agencias financiadoras | Ministerio de Ciencia e Innovación (MICIN). España |
Identificador del proyecto | RTI2018-098062-A-I00 |
Cita | Fernández Cerero, D., Ortega Rodríguez, F.J., Jakóbik, A. y Fernández Montes González, A. (2021). DISCERNER: Dynamic selection of resource manager in hyper-scale cloud-computing data centres. Future Generation Computer Systems, 116 (March 2021), 190-199. |
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