publication . Article . Other literature type . 2019

MAGNETIC: Multi-Agent Machine Learning-Based Approach for Energy Efficient Dynamic Consolidation in Data Centers

Kawsar Haghshenas; Ali Pahlevan; Marina Zapater; Siamak Mohammadi; David Atienza;
Open Access
  • Published: 05 Jun 2019
  • Country: Switzerland
Improving the energy efficiency of data centers while guaranteeing Quality of Service (QoS), together with detecting performance variability of servers caused by either hardware or software failures, are two of the major challenges for efficient resource management of large-scale cloud infrastructures. Previous works in the area of dynamic Virtual Machine (VM) consolidation are mostly focused on addressing the energy challenge, but fall short in proposing comprehensive, scalable, and low-overhead approaches that jointly tackle energy efficiency and performance variability. Moreover, they usually assume over-simplistic power models, and fail to accurately conside...
free text keywords: Distributed computing, Quality of service, Virtual machine, computer.software_genre, computer, Energy consumption, Server, Efficient energy use, Machine learning, Data center, business.industry, business, Scalability, Cloud computing, Artificial intelligence, Computer science
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