Proactive dynamic virtual-machine consolidation for energy conservation in cloud data centres
Salam Ismaeel,Raed Karim,Ali Miri +2 more
- Vol. 7, Iss: 1, pp 10
TLDR
This paper provides an in-depth survey of the most recent techniques and algorithms used in proactive dynamic VM consolidation focused on energy consumption and presents a general framework that can be used on multiple phases of a complete consolidation process.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.read more
Citations
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Proceedings ArticleDOI
Reduced Energy Consumption in Cloud Data Center Using Machine Learning Algorithm Load Balancing
TL;DR: In this article , the authors present an in-depth study of the patterns of energy consumption exhibited by cloud-based systems and present an analysis of energy use and show how suitable optimization methods based on energy consumption can assist cloud data centres in saving even more electricity.
A Method for Measuring Energy Consumption in IaaS Cloud
TL;DR: An experimental approach of measuring power consumption as a result of executing application workloads in IaaS cloud, based on Intel’s Running Average Power Limit (RAPL) interface is proposed, which can be used to study the effect of workload consolidation on CPU and I/O performance by varying the number of Virtual Machines (VMs).
Journal ArticleDOI
Causes of Energy Wastage in Cloud Data Centre Servers : A Survey
TL;DR: This paper elaborate on the concept of cloud computing and virtualization, and presents a survey of the main causes of energy wastage in datacenter servers as well as proposed solutions to address the problem.
Dissertation
Energy E cient Virtual Machine Placement Algorithms in OpenStack Neat
TL;DR: This work proposes VM placement algorithms based on both bin-packing heuristics and servers’ power efficiency and introduces a new binpacking heuristic called a Medium-Fit (MF) to reduce SLA violation and VM migrations.
Journal ArticleDOI
Virtual Machine Consolidation Method with Low Delay and Energy Consumption Parameters
TL;DR: The proposed method is built on a fuzzy logic with consolidation framework and filters the virtual machine from an overloaded host and the migration control mechanism build into the system helps in increasing the performance for the selection process.
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