scholarly journals A Multi Criteria-Based Approach for Virtual Machines Consolidation to Save Electrical Power in Cloud Data Centers

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 24110-24117 ◽  
Author(s):  
Mohammed Amoon
Keyword(s):  
Data Centers ◽  
Virtual Machines ◽  
Electrical Power ◽  
Cloud Data ◽  
Cloud Data Centers

scholarly journals Energy-Efficient Consolidation of Virtual Machines in Cloud Data Centers

2019 ◽  
Vol 8 (6) ◽  
pp. 446-449
Keyword(s):  
Data Centers ◽  
Virtual Machines ◽  
Electrical Power ◽  
Operating Cost ◽  
Huge Amount ◽  
Rapid Reduction ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Operational Expenditure ◽  
Capacity Performance

The lightning increase in demand of computational power consumed by modern applications has made us to shift for Cloud Computing Model which has led to establish very largescaled virtualized Data Centers. Such Data Centers consumes huge amount of electrical power which results to high Operating cost and Carbon-di-oxide emission.The servers in Data Centers consume/waste a substantial amount of energy/power. Since servers are deployed and configured for peak capacity, performance, usually at the expense of efficiency. Such waste increases the capital and operational expenditure which can result in power and space being exhausted, which creates a situation where the organization may grow in data centers.Consolidating and Virtualizing servers can increase overall utilization of resources from 10% to 30%. The rapid reduction in capital and expenditure can motivate many organizations to virtualize the servers.

scholarly journals Dynamic Management of Virtual machines for Server Consilidation in Data Centers

2019 ◽  
Author(s):  
Girish L
Keyword(s):  
Data Centers ◽  
Virtual Machines ◽  
Electrical Power ◽  
Cloud Platform ◽  
Computing Technology ◽  
Cloud Data ◽  
On Demand ◽  
The World ◽  
Cloud Data Centers ◽  
Migration Technique

Cloud computing technology whichprovides computing resource on demand over the internet as aservice. To meet this requirement virtualized data centers areestablished all around the world. However, data centers utilizelarge amount of electrical power. Thus results in high operatingcosts and emits carbon dioxide to environment. Carbon dioxideemitted from cloud data centers cause global warming.This paper provides a model and techniques for thedynamic management virtual machines in data centers. The mainpurpose is to increase the utilization of computing resources andminimize energy consumption by switching off the idle nodes.Live migration technique, moving virtual machines betweendifferent physical servers, is mainly used to reduce the number ofactive compute nodes in cloud data centers with minimaldowntime. In this paper, we provide an architecture and softwareframework of open stack neat, for dynamic virtual machineconsolidation in open stack cloud deployment. Open stack is anopen source cloud platform which provides infrastructure as aservice solution. Open stack allows users to deploy virtualmachines which manages different workloads.

An Energy-Efficient Consolidation of Virtual Machines in Cloud Data Centers

2017 ◽  
Vol 26 (1) ◽  
pp. 113-128
Author(s):  
Gamal Eldin I. Selim ◽  
Mohamed A. El-Rashidy ◽  
Nawal A. El-Fishawy
Keyword(s):  
Energy Efficient ◽  
Data Centers ◽  
Virtual Machines ◽  
Cloud Data ◽  
Cloud Data Centers

scholarly journals Virtual Machine Placement via Bin Packing in Cloud Data Centers

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 389 ◽  
Author(s):  
Aisha Fatima ◽  
Nadeem Javaid ◽  
Tanzeela Sultana ◽  
Waqar Hussain ◽  
Muhammad Bilal ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Data Centers ◽  
Bin Packing ◽  
Virtual Machines ◽  
Particle Swarm ◽  
Vm Placement ◽  
Swarm Optimization ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Vm Consolidation

With the increasing size of cloud data centers, the number of users and virtual machines (VMs) increases rapidly. The requests of users are entertained by VMs residing on physical servers. The dramatic growth of internet services results in unbalanced network resources. Resource management is an important factor for the performance of a cloud. Various techniques are used to manage the resources of a cloud efficiently. VM-consolidation is an intelligent and efficient strategy to balance the load of cloud data centers. VM-placement is an important subproblem of the VM-consolidation problem that needs to be resolved. The basic objective of VM-placement is to minimize the utilization rate of physical machines (PMs). VM-placement is used to save energy and cost. An enhanced levy-based particle swarm optimization algorithm with variable sized bin packing (PSOLBP) is proposed for solving the VM-placement problem. Moreover, the best-fit strategy is also used with the variable sized bin packing problem (VSBPP). Simulations are done to authenticate the adaptivity of the proposed algorithm. Three algorithms are implemented in Matlab. The given algorithm is compared with simple particle swarm optimization (PSO) and a hybrid of levy flight and particle swarm optimization (LFPSO). The proposed algorithm efficiently minimized the number of running PMs. VM-consolidation is an NP-hard problem, however, the proposed algorithm outperformed the other two algorithms.

Multidimensional Resource Scheduling in Cloud Data Centers

2014 ◽  
Vol 1008-1009 ◽  
pp. 1513-1516
Author(s):  
Hai Na Song ◽  
Xiao Qing Zhang ◽  
Zhong Tang He
Keyword(s):  
Cloud Computing ◽  
Data Centers ◽  
Bin Packing ◽  
Virtual Machines ◽  
Three Dimensional ◽  
Resource Scheduling ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Cloud Data ◽  
Cloud Data Centers

Cloud computing environment is regarded as a kind of multi-tenant computing mode. With virtulization as a support technology, cloud computing realizes the integration of multiple workloads in one server through the package and seperation of virtual machines. Aiming at the contradiction between the heterogeneous applications and uniform shared resource pool, using the idea of bin packing, the multidimensional resource scheduling problem is analyzed in this paper. We carry out some example analysis in one-dimensional resource scheduling, two-dimensional resource schduling and three-dimensional resource scheduling. The results shows that the resource utilization of cloud data centers will be improved greatly when the resource sheduling is conducted after reorganizing rationally the heterogeneous demands.

Bandwidth allocation for communicating virtual machines in cloud data centers

2020 ◽  
Vol 76 (9) ◽  
pp. 7268-7289
Author(s):  
Kamalesh Karmakar ◽  
Rajib K. Das ◽  
Sunirmal Khatua
Keyword(s):  
Bandwidth Allocation ◽  
Data Centers ◽  
Virtual Machines ◽  
Cloud Data ◽  
Cloud Data Centers

scholarly journals Virtual Machine Consolidation with Minimization of Migration Thrashing for Cloud Data Centers

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xialin Liu ◽  
Junsheng Wu ◽  
Gang Sha ◽  
Shuqin Liu
Keyword(s):  
Virtual Machine ◽  
Carbon Dioxide Emissions ◽  
Data Centers ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
High Capacity ◽  
Electrical Energy ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Vm Consolidation

Cloud data centers consume huge amount of electrical energy bringing about in high operating costs and carbon dioxide emissions. Virtual machine (VM) consolidation utilizes live migration of virtual machines (VMs) to transfer a VM among physical servers in order to improve the utilization of resources and energy efficiency in cloud data centers. Most of the current VM consolidation approaches tend to aggressive-migrate for some types of applications such as large capacity application such as speech recognition, image processing, and decision support systems. These approaches generate a high migration thrashing because VMs are consolidated to servers according to VM’s instant resource usage without considering their overall and long-term utilization. The proposed approach, dynamic consolidation with minimization of migration thrashing (DCMMT) which prioritizes VM with high capacity, significantly reduces migration thrashing and the number of migrations to ensure service-level agreement (SLA) since it keeps VMs likely to suffer from migration thrashing in the same physical servers instead of migrating. We have performed experiments using real workload traces compared to existing aggressive-migration-based solutions; through simulations, we show that our approach improves migration thrashing metric by about 28%, number of migrations metric by about 21%, and SLAV metric by about 19%.

scholarly journals Server Consolidation Based on Culture Multiple-Ant-Colony Algorithm in Cloud Computing

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2724 ◽  
Author(s):  
Yuan ◽  
Sun
Keyword(s):  
Energy Consumption ◽  
Virtual Machine ◽  
Ant Colony Algorithm ◽  
Data Centers ◽  
Virtual Machines ◽  
Ant Colony ◽  
Virtual Machine Migration ◽  
Server Consolidation ◽  
Cloud Data ◽  
Cloud Data Centers

High-energy consumption in data centers has become a critical issue. The dynamic server consolidation has significant effects on saving energy of a data center. An effective way to consolidate virtual machines is to migrate virtual machines in real time so that some light load physical machines can be turned off or switched to low-power mode. The present challenge is to reduce the energy consumption of cloud data centers. In this paper, for the first time, a server consolidation algorithm based on the culture multiple-ant-colony algorithm was proposed for dynamic execution of virtual machine migration, thus reducing the energy consumption of cloud data centers. The server consolidation algorithm based on the culture multiple-ant-colony algorithm (CMACA) finds an approximate optimal solution through a specific target function. The simulation results show that the proposed algorithm not only reduces the energy consumption but also reduces the number of virtual machine migration.

Sign in / Sign up

Export Citation Format

Share Document