Application-aware Virtual Machine Provision Strategy
Date Issued
2012
Date
2012
Author(s)
Yang, Jyun-Shiung
Abstract
Energy consumption of data centers is an important issue in cloud
computing, therefore it is important to develop energy conservation
algorithms to reduce energy consumption of data centers. Most energy
conservation algorithms achieve its goal by consolidating workload,
reducing the number of underutilized servers, and shutting idle
servers.
An energy conservation algorithm must address two issues. The first
issue is the placement of virtual machine image. If the physical
machine that stores the image is off-line, then we cannot run this
virtual machine. The second issue is the characteristics of virtual
machines. We observe that the performance of an I/O-intensive virtual
machine running on the physical machine without its image is only 40\%
of the performance while running on the physical machine {em with}
its image. On the other hand, the performance of a CPU-intensive
virtual machine is almost the same whether the physical machine has
the image or not.
This paper describes our energy conservation algorithms as enhancement
of Roystonea, which is a cloud computing system that manages crucial
resources in a cloud system. We propose an approximation algorithm
and two dynamic programmings to consolidate images of virtual
machines, and find the number of physical machines that need to be
stored images. We conduct simulations and compare the number of
physical machines that need to be stored images in approximation
algorithm with the optimal number of physical machines found by the
dynamic programming. The simulation results indicate that our
approximation algorithm can find good solutions in much less time than
the dynamic programming.
Subjects
Cloud Computing
Energy Conservation
Image Consolidation
SDGs
Type
thesis
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