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
More filters
Journal ArticleDOI
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.
Journal ArticleDOI
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
More filters
Proceedings ArticleDOI
RPPS: A Novel Resource Prediction and Provisioning Scheme in Cloud Data Center
TL;DR: RPPS (Cloud Resource Prediction and Provisioning scheme), a scheme that automatically predict future demand and perform proactive resource provisioning for cloud applications, employs the ARIMA model to predict the workloads in the future, combines both coarse- grained and fine-grained resource scaling under different situations, and adopts a VM-complementary migration strategy.
Journal ArticleDOI
Novel resource allocation algorithms to performance and energy efficiency in cloud computing
TL;DR: A novel QoS-aware VMs consolidation approach is proposed that adopts a method based on resource utilization history of virtual machines that shows improvement in QoS metrics and energy consumption as well as demonstrate that there is a trade-off between energy consumption and quality of service in the cloud environment.
Journal ArticleDOI
Toward energy-efficient cloud computing: Prediction, consolidation, and overcommitment
TL;DR: Key resource allocation challenges are highlighted, and some potential solutions to reduce cloud data center energy consumption are presented, and special focus is given to power management techniques that exploit the virtualization technology to save energy.
Journal ArticleDOI
A survey on data center networking for cloud computing
TL;DR: An overview of data center networks for cloud computing and evaluate construction prototypes based on these issues is presented, specifically, detailed descriptions of several important aspects: the physical architecture, virtualized infrastructure, and DCN routing.
Journal ArticleDOI
Novel energy and SLA efficient resource management heuristics for consolidation of virtual machines in cloud data centers
TL;DR: The results of simulations using Cloudsim simulator validates the applicability of the proposed policies which shows up to 46, 99, and 95% reductions in energy consumption, SLA violation, and number of VM migrations, respectively in comparison with state of the arts.
Related Papers (5)
Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers
Anton Beloglazov,Rajkumar Buyya +1 more