Abstract
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.
Highlights
Recent years has seen an exponential increase in the use of the cloud computing industry in satisfying Information Technology (IT) requirements
This paper presents a comprehensive survey and analysis work on Virtual Machines (VMs) consolidation focusing on energy consumption in Cloud data centre (CDC)
The paper focuses on proactive dynamic VM consolidations in CDCs with heterogeneous environments
Summary
Recent years has seen an exponential increase in the use of the cloud computing industry in satisfying Information Technology (IT) requirements. Clustering Process The objective of the prediction subsystem is to use previous usage patterns to estimate future VM request workloads in a data center.
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