Journal
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
Volume 7, Issue -, Pages -Publisher
SPRINGEROPEN
DOI: 10.1186/s13677-018-0111-x
Keywords
Cloud computing; Data centre management; Workload prediction; Energy efficiency; VM placement; Review
Categories
Funding
- Department of Computer Science at Ryerson University
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Data center power consumption is among the largest commodity expenditures for many organizations. Reduction of power used in cloud data centres with heterogeneous physical resources can be achieved through Virtual-Machine (VM) consolidation which reduces the number of Physical Machines (PMs) used, subject to Quality of Service (QoS) constraints. This paper provides an in-depth survey of the most recent techniques and algorithms used in proactive dynamic VM consolidation focused on energy consumption. We present a general framework that can be used on multiple phases of a complete consolidation process.
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