Stochastic Virtual Machine Placement for Cloud Data Centers Under Resource Requirement Variations
نویسندگان
چکیده
منابع مشابه
Multicore virtual machine placement in cloud data centers ∗
Finding the best way to map virtual machines (VMs) to physical machines (PMs) in a cloud data center is an important optimization problem, with significant impact on profitability, performance, and energy consumption. In most situations, the computational capacity of PMs and the computational load of VMs are a vital aspect to consider in the VM-to-PM mapping. Previous work modeled computational...
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The problem of high energy consumption is becoming more and more serious due to the construction of large-scale cloud data centers. In order to reduce the energy consumption and SLA violation, a new virtual machine (VM) placement algorithm named ATEA (adaptive three-threshold energy-aware algorithm), which takes good use of the historical data from resource usage by VMs, is presented. In ATEA, ...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2019.2957340