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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Energy-aware VM placement algorithms for the OpenStack Neat consolidation framework
TL;DR: This work proposes VM placement algorithms based on both bin-packing heuristics and servers’ power efficiency and introduces a new bin- packing heuristic called a Medium-Fit (MF) to reduce SLA violation.
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A Neuro-fuzzy approach for user behaviour classification and prediction
Atta-ur-Rahman,Sujata Dash,Ashish Kumar Luhach,Naveen Chilamkurti,Seungmin Baek,Yunyoung Nam +5 more
TL;DR: A neuro-fuzzy approach for the classification and prediction of user behaviour is proposed and the scheme is found to be promising in terms of classification as well as prediction accuracy.
Journal ArticleDOI
A survey of data center consolidation in cloud computing systems
Leila Helali,Mohamed Nazih Omri +1 more
TL;DR: In this article, the authors present an overview of virtualized data centers and consolidation solutions from the literature and present a brief thematic taxonomy and an illustration of some consolidation solutions.
Journal ArticleDOI
Embedding individualized machine learning prediction models for energy efficient VM consolidation within Cloud data centers
Seyedhamid Mashhadi Moghaddam,Michael O'Sullivan,Cameron Walker,Sareh Fotuhi Piraghaj,Charles P. Unsworth +4 more
TL;DR: This paper proposes an energy aware VM consolidation algorithm that minimizes SLAVs and develops different fine-tuned Machine Learning prediction models for individual VMs to predict the best time to trigger migrations from hosts.
Journal ArticleDOI
Deep reinforcement learning for multi-objective placement of virtual machines in cloud datacenters
TL;DR: This work introduces a multi-objective approach to compute optimal placement strategies considering different goals, such as the impact of hardware outages, the power required by the datacenter, and the performance perceived by users.
References
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Posted Content
Performance-oriented Cloud Provisioning: Taxonomy and Survey
Yasir Shoaib,Olivia Das +1 more
TL;DR: A detailed literature survey of dynamic provisioning within cloud systems with focus on application performance is provided, which views provisioning from different perspectives, aiding in understanding the process inside-out.
Proceedings ArticleDOI
An Adaptive VM Provisioning Method for Large-Scale Agent-Based Traffic Simulations on the Cloud
TL;DR: A method for efficient utilization of computational resources for distributed agent-based simulations, providing a mechanism that adapts the resource provisioning to users' objectives and workload evolution, and a staged asynchronous migration technique to limit the migration overhead when the number of workers change are proposed.
Proceedings ArticleDOI
Dynamic Virtual Machine Consolidation: A Multi Agent Learning Approach
TL;DR: This paper proposes a cooperative multi agent learning approach to tackle the energy-performance tradeoff in cloud data centers in comparison to state-of-the-art algorithms.
Proceedings ArticleDOI
Task shape classification and workload characterization of google cluster trace
TL;DR: This work presents a simple technique for constructing workload characteristics and also provides production insights into understanding workload performance in cluster machine.
Book ChapterDOI
Multi-objective virtual machine selection for migrating in virtualized data centers
TL;DR: A multi-objective optimization model based on detailed analysis of the impact of CPU temperature, resource usage and power consumption in VM selection is proposed and a VM selection algorithm is developed to optimize the synthesized effect of VM migration, which will ultimately improve the system performance of physical machines (PMs).
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