Proactive dynamic virtual-machine consolidation for energy conservation in cloud data centres

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, s...

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Veröffentlicht in:Journal of cloud computing : advances, systems and applications Jg. 7; H. 1; S. 1 - 28
Hauptverfasser: Ismaeel, Salam, Karim, Raed, Miri, Ali
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 18.06.2018
Springer Nature B.V
SpringerOpen
Schlagworte:
Cloud computing
Computer Communication Networks
Computer Science
Computer System Implementation
Computer Systems Organization and Communication Networks
Consolidation
Data centers
Data centre management
Energy conservation
Energy consumption
Energy efficiency
Expenditures
Information Systems Applications (incl.Internet)
Power consumption
Review
Software Engineering/Programming and Operating Systems
Special Purpose and Application-Based Systems
Virtualization
VM placement
Workload prediction
Cloud computing
Data centre management
Energy efficiency
Review
Workload prediction
VM placement
ISSN:2192-113X, 2192-113X
Online-Zugang:Volltext
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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:2192-113X
2192-113X
DOI:10.1186/s13677-018-0111-x