DISCERNER: Dynamic selection of resource manager in hyper-scale cloud-computing data centres
| Autor: | Agnieszka Jakóbik, F. Javier Ortega, Alejandro Fernández-Montes, Damián Fernández-Cerero |
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| Rok vydání: | 2021 |
| Předmět: |
Computer Networks and Communications
business.industry Computer science Corporate governance Distributed computing 020206 networking & telecommunications Cloud computing 02 engineering and technology Business model Hardware and Architecture 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Resource management The Internet Software system Performance indicator business Classifier (UML) Software |
| Zdroj: | Future Generation Computer Systems. 116:190-199 |
| ISSN: | 0167-739X |
| DOI: | 10.1016/j.future.2020.10.031 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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