scholarly journals iVMp: An Interactive VM Placement Algorithm for Agile Capital Allocation

2013 ◽  
Author(s):  
Xi Li ◽  
Anthony Ventresque ◽  
Nicola Stokes ◽  
James Thorburn ◽  
John Murphy
Keyword(s):  
Capital Allocation ◽  
Vm Placement ◽  
Placement Algorithm

scholarly journals A Access of MBFD, Percentage Util, Absolute Capacity and BSP VM Placement Algorithm on Cloud Datacenter

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1782-1786
Keyword(s):  
Virtual Machine ◽  
Vm Placement ◽  
Dynamic Provisioning ◽  
Works Of Art ◽  
Cloud Datacenter ◽  
Placement Algorithm

The datacenter control admission is expanding hurriedly because of the versatility and dynamic provisioning of benefits. The debasement in like manner generally execution, effect of surroundings are the vital inconveniences in datacenter for the blast in power utilization. The power benefited from by method for unused host device to be turned off, through combining the virtual gadget powerfully to keep control in datacenter. on this paper we have conversely 4 specific virtual machine situation set of rules for the quality utilization, amount of VM movement, SLA infringement (SLAV), in general execution debasement in view of Migration (PDM), SLA infringement Time in accordance with vigorous host (SLATAH) and power SLA infringement (ESV). to assess the arrangement of guidelines we have utilized the CloudSim recreation toolbox and true works of art burden lines of planet lab VMs for our examination.

Energy and SLA Efficient Virtual Machine Placement in Cloud Environment Using Non-Dominated Sorting Genetic Algorithm

2021 ◽  
pp. 773-789
Author(s):  
Oshin Sharma ◽  
Hemraj Saini
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Data Centers ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Vm Placement ◽  
Energy Consumption Reduction ◽  
Consumption Reduction ◽  
The World ◽  
Placement Algorithm

To increase the availability of the resources and simultaneously to reduce the energy consumption of data centers by providing a good level of the service are one of the major challenges in the cloud environment. With the increasing data centers and their size around the world, the focus of the current research is to save the consumption of energy inside data centers. Thus, this article presents an energy-efficient VM placement algorithm for the mapping of virtual machines over physical machines. The idea of the mapping of virtual machines over physical machines is to lessen the count of physical machines used inside the data center. In the proposed algorithm, the problem of VM placement is formulated using a non-dominated sorting genetic algorithm based multi-objective optimization. The objectives are: optimization of the energy consumption, reduction of the level of SLA violation and the minimization of the migration count.

scholarly journals An Distributed Virtual Machine Placement Algorithm for Balanced Resource Utilization and Low Energy Consumption

2018 ◽  
Vol 173 ◽  
pp. 03092
Author(s):  
Bo Li ◽  
Yun Wang
Keyword(s):  
Virtual Machine ◽  
Data Centers ◽  
Virtual Machine Placement ◽  
Vm Placement ◽  
Energy Aware ◽  
Cloud Data ◽  
Low Energy Consumption ◽  
Cloud Data Centers ◽  
Placement Algorithm ◽  
Heterogeneous Cloud

Virtual machine placement is the process of selecting the most suitable server in large cloud data centers to deploy newly-created VMs. Traditional load balancing or energy-aware VM placement approaches either allocate VMs to PMs in centralized manner or ignore PM’s cost-capacity ratio to implement energy-aware VM placement. We address these two issues by introducing a distributed VM placement approach. A auction-based VM placement algorithm is devised for help VM to find the most suitable server in large heterogeneous cloud data centers. Our algorithm is evaluated by simulation. Experimental results show two major improvements over the existing approaches for VM placement. First, our algorithm efficiently balances the utilization of multiple types of resource by minimizing the amount of physical servers used. Second, it reduces system cost compared with existing approaches in heterogeneous environment.

A Virtual Machine Placement Algorithm with Energy-Efficiency in Cloud Computing

2017 ◽  
Vol 8 (2) ◽  
pp. 20-36
Author(s):  
Yu Cai
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Virtual Machines ◽  
Live Migration ◽  
Vm Placement ◽  
Server Cluster ◽  
Simulated Environment ◽  
Resource Requirements ◽  
Placement Algorithm

Energy efficient virtual machines (VM) management and distribution on cloud platforms is an important research subject. Mapping VMs into PMs (Physical Machines) requires knowing the capacity of each PM and the resource requirements of the VMs. It should also take into accounts of VM operation overheads, the reliability of PMs, Quality of Service (QoS) in addition to energy efficiency. In this article, the authors propose an energy efficient statistical live VM placement scheme in a heterogeneous server cluster. Their scheme supports VM requests scheduling and live migration to minimize the number of active servers in order to save the overall energy in a virtualized server cluster. Specifically, the proposed VM placement scheme incorporates all VM operation overheads in the dynamic migration process. In addition, it considers other important factors in relation to energy consumption and is ready to be extended with more considerations on user demands. The authors conducted extensive evaluations based on HPC jobs in a simulated environment. The results prove the effectiveness of the proposed scheme.

scholarly journals A Access of MBFD, Logo Allocator, MINLP and MWFDVP VM Placement Algorithm on Cloud Datacenter

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1787-1791
Keyword(s):  
Vm Placement ◽  
Works Of Art ◽  
Cloud Datacenter ◽  
Placement Algorithm ◽  
Advanced System

allotted computing offers the distinct assets oninterest for the prevent customers on pay with regards to utilize via net affiliation. This has advanced the interest for figuring sources precept to the development of power intake inward datacenters. the most important undertaking is the means via which to dependability the blessings by diminishing the power usage associated with SLA. Powerfully merging the advanced contraption, which places the inert hubs to paintings hubs or switches off the unused host tool in datacenters by way of methods for relocating the virtual gadget stay from underloaded or over-burden have device. in this paper we've in examination 4 diverse advanced system arrangement set of concepts for the electricity intake, scope of VM relocation, SLA infringement (SLAV), execution debasement in light of Migration (PDM), SLA infringement Time according to dynamic host (SLATAH) and strength SLA infringement (ESV). to evaluate the association of ideas we've utilized the CloudSim activity toolbox and actual international works of art burden traces of planet lab VMs for our trial.

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