An energy-aware heuristic framework for virtual machine consolidation in Cloud computing

Cao, Zhibo; Dong, Shoubin

doi:10.1007/s11227-014-1172-3

Cited by 63 publications

(30 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, Cao et al [11] have proposed two novel VM selection policies, which are the MinPower (MP) and MaxUtilization (MU), respectively. Proposed in CloudSim, MP, and MU aim at finding an appropriate placement for the migrated VMs.…”

Section: B Selection Policy Of Migrated Vmmentioning

confidence: 99%

“…CM2 adopts DTP in the determination policy of VM migration timing and Weighted Optimization (WO) policy in the determination policy of the destination servers. More- [11] have also investigated a combined optimization policy. However, it only considers the overloading migration in the determination of VM migration timing and neglects the underloading migration.…”

Section: Combined Vm Migration Policymentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive Evaluation of Scheduling Methods of Virtual Machine Migration for Energy Conservation

Wang

et al. 2017

IEEE Systems Journal

View full text Add to dashboard Cite

Scheduling methods of virtual machine (VM) migration are regarded as an effective way for energy conservation. A number of scheduling methods of VM migration have been proposed and/or improved in several research works. However, none of the scheduling methods was evaluated from a comprehensive viewpoint, and there is no useful reference for practices of energy conservation in various data centers. In order to provide a useful reference for best practices of energy conservation in various data centers, this paper presents the first comprehensive evaluation of scheduling methods of VM migration. After giving an overview of major optimization problems, this paper proposes a new set of evaluation metrics that can be used in the evaluation of various scheduling methods of VM migration from different aspects, presents an evaluation environment we constructed according to our evaluation metrics, and discusses evaluation results of those proposed scheduling methods on our evaluation environment. The results of our comprehensive evaluation show that the proposed evaluation metrics can reflect the merits and demerits of various scheduling methods from the perspective of different data center scales and divergent workload types and therefore can be used for evaluating the scheduling methods of VM migration fairly and reasonably.

show abstract

Section: B Selection Policy Of Migrated Vmmentioning

confidence: 99%

Section: Combined Vm Migration Policymentioning

confidence: 99%

A Comprehensive Evaluation of Scheduling Methods of Virtual Machine Migration for Energy Conservation

Wang

et al. 2017

IEEE Systems Journal

View full text Add to dashboard Cite

show abstract

“…Linear programming and heuristics are used for VM migration, which helps in prioritising VMs with fixed capacity [14]. In [15], an energy-aware heuristic framework is proposed for VMs to maintain SLAs and to use minimum power for maximum utilisation.…”

Section: Literature Surveymentioning

confidence: 99%

Web Server Performance Evaluation in a Virtualisation Environment

Kolhar¹

2017

ijacsa

View full text Add to dashboard Cite

Abstract-Operational and investment costs are reduced by resource sharing in virtual machine (VM) environments, which also results in an overhead for hosted services. VM machine performance is important because of resource contention. If an application takes a long time to execute because of its CPU or network, it is considered to be a failure because if many VMs are running over a single hardware platform, there will be competition for shared resources, e.g., the CPU, network bandwidth, and memory. Therefore, this study focuses on measuring the performance of a web server under a virtual environment and comparing those results with that from a dedicated machine. We found that the difference between the two sets of results is largely negligible. However, in some areas, one approach performed better than the other.

show abstract

“…Cao, Z et.al [3] proposed a framework for VM consolidation. They also use many method for overload detection and VM selection.…”

Section: Related Workmentioning

confidence: 99%

“…Cloud computing delivers a pool of abstracted and virtualized resources including computing power, storage, platforms and software applications over the Internet based on users demand [1].This pool of resources is provisioned as a very high availability and Quality of Service (QoS) are offered by the cloud infrastructure provider by means of service level agreements (SLA) [2] These services may be categorized as infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS) [3] and also available in three deployment models viz.…”

Section: Introductionmentioning

confidence: 99%

Workload Consolidation using VM Selection and Placement Techniques in Cloud Computing

Patel¹,

Patel²,

Patel³

2016

IJCA

View full text Add to dashboard Cite

Cloud computing provides a consumer pay-per-use computing model over the Internet using numerous data centers across the globe. Power consumption by the huge data centers in Cloud environment has attracted the attention of research community. Efficient usage of energy in Cloud can be addressed in many facets. Virtual Machine (VM) consolidation is one of the techniques to save or reduce energy in virtualized data centers. VM Migration in Cloud also provides us an opportunity for reducing energy consumption. In this research, we intend to study various VM placements & selection policies and VM migration algorithms for underloaded and overloaded hosts to reduce energy consumption and SLA violation. We propose a novel method using combination of two methods, Least Increase Power (LIP) consumption with Host Sort and Minimum Correlation Coefficient (MCC) for consolidation of VM placement, placing a migratable VM on a host based on utilization thresholds. The results show performance of each combination of algorithms varies with the changing value of the parameters brings better in terms of energy consumption, VM migration time and SLA violation. The reader may plunge the appropriate method for energy consumption.

show abstract

An energy-aware heuristic framework for virtual machine consolidation in Cloud computing

Cited by 63 publications

References 18 publications

A Comprehensive Evaluation of Scheduling Methods of Virtual Machine Migration for Energy Conservation

A Comprehensive Evaluation of Scheduling Methods of Virtual Machine Migration for Energy Conservation

Web Server Performance Evaluation in a Virtualisation Environment

Workload Consolidation using VM Selection and Placement Techniques in Cloud Computing

Contact Info

Product

Resources

About