scholarly journals A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Gaochao Xu ◽  
Yan Ding ◽  
Jia Zhao ◽  
Liang Hu ◽  
Xiaodong Fu
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Artificial Bee Colony ◽  
Power Saving ◽  
Bayes Theorem ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Vm Migration ◽  
Cloud Data ◽  
Bee Colony

Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration’s ability and local exploitation’s ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.

scholarly journals A Location Selection Policy of Live Virtual Machine Migration for Power Saving and Load Balancing

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Jia Zhao ◽  
Yan Ding ◽  
Gaochao Xu ◽  
Liang Hu ◽  
Yushuang Dong ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Power Saving ◽  
Genetic Operators ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Vm Migration ◽  
Location Selection ◽  
Cloud Data

Green cloud data center has become a research hotspot of virtualized cloud computing architecture. And load balancing has also been one of the most important goals in cloud data centers. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on location selection (migration policy) of live VM migration for power saving and load balancing. We propose a novel approach MOGA-LS, which is a heuristic and self-adaptive multiobjective optimization algorithm based on the improved genetic algorithm (GA). This paper has presented the specific design and implementation of MOGA-LS such as the design of the genetic operators, fitness values, and elitism. We have introduced the Pareto dominance theory and the simulated annealing (SA) idea into MOGA-LS and have presented the specific process to get the final solution, and thus, the whole approach achieves a long-term efficient optimization for power saving and load balancing. The experimental results demonstrate that MOGA-LS evidently reduces the total incremental power consumption and better protects the performance of VM migration and achieves the balancing of system load compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.

A Hybrid Approach for Virtual Machine Migration in Cloud Computing Environment

2017 ◽  
Vol 7 (9) ◽  
pp. 30 ◽  
Author(s):  
Ramandeep Kaur
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Heuristic Algorithms ◽  
Hybrid Approach ◽  
Cloud Infrastructure ◽  
Virtual Machine Migration ◽  
Bee Colony ◽  
Effective Manner ◽  
Effective Performance

A lot of research has been done in the field of cloud computing in computing domain.  For its effective performance, variety of algorithms has been proposed. The role of virtualization is significant and its performance is dependent on VM Migration and allocation. More of the energy is absorbed in cloud; therefore, the utilization of numerous algorithms is required for saving energy and efficiency enhancement in the proposed work. In the proposed work, green algorithm has been considered with meta heuristic algorithms, ABC (Artificial Bee colony .Every server has to perform different or same functions. A cloud computing infrastructure can be modelled as Primary Machineas a set of physical Servers/host PM1, PM2, PM3… PMn. The resources of cloud infrastructure can be used by the virtualization technology, which allows one to create several VMs on a physical server or host and therefore, lessens the hardware amount and enhances the resource utilization. The computing resource/node in cloud is used through the virtual machine. To address this problem, data centre resources have to be managed in resource -effective manner for driving Green Cloud computing that has been proposed in this work using Virtual machine concept with ABC and Neural Network optimization algorithm. The simulations have been carried out in CLOUDSIM environment and the parameters like SLA violations, Energy consumption and VM migrations along with their comparison with existing techniques will be performed.

scholarly journals FHCS: Hybridised optimisation for virtual machine migration and task scheduling in cloud data center

2020 ◽  
Vol 14 (12) ◽  
pp. 1942-1948
Author(s):  
Banavath Balaji Naik ◽  
Dhananjay Singh ◽  
Arun B. Samaddar
Keyword(s):  
Virtual Machine ◽  
Task Scheduling ◽  
Data Center ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Cloud Data ◽  
And Task

scholarly journals A Mobility-Oriented Scheme for Virtual Machine Migration in Cloud Data Center Network

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 8327-8337 ◽  
Author(s):  
Bo Hu ◽  
Shanzhi Chen ◽  
Jianye Chen ◽  
Zhangfeng Hu
Keyword(s):  
Virtual Machine ◽  
Data Center ◽  
Data Center Network ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Cloud Data

scholarly journals Role of Different Integer Virtual Machine in Cloud Data Center

2019 ◽  
Vol 3 (4) ◽  
Author(s):  
Arif Ullah ◽  
Nazri Mohd Nawi ◽  
Hairulnizam Bin Mahdin ◽  
Samad Baseer ◽  
Mustafa Mat Deris
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Data Center ◽  
Network Stability ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Energy Processing ◽  
Data Centres ◽  
Stability Energy

In modern data centres of cloud computing contains virtualization system. In order to improve network stability, energy efficiency, and makespan proper virtualization need. The virtual machine is one of the examples of virtualizations. Cloud computing data centres consist of millions of virtual machine to manage load balancing. In this study check the different number of virtual machine role in data centres, for that purpose, we established a network with the help of cloudsim and compare different data centres at each zones taking a different number of the virtual machine with different paramater and network banwith.After the simulation the result shows that increasning in the number of VM can affect the netwok accuracy in term of energy ,processing time ,coast and network stabality . 

scholarly journals PEMILIHAN DAN MIGRASI VM MENGGUNAKAN MCDM UNTUK PENINGKATAN KINERJA LAYANAN PADA CLOUD COMPUTING

2016 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdullah Fadil ◽  
Waskitho Wibisono
Keyword(s):  
Decision Making ◽  
Cloud Computing ◽  
Virtual Machine ◽  
Data Center ◽  
Response Times ◽  
Multi Criteria Decision Making ◽  
Live Migration ◽  
Vm Placement ◽  
Cloud Data Center ◽  
Cloud Data

Komputasi awan atau cloud computing merupakan lingkungan yang heterogen dan terdistribusi, tersusun atas gugusan jaringan server dengan berbagai kapasitas sumber daya komputasi yang berbeda-beda guna menopang model layanan yang ada di atasnya. Virtual machine (VM) dijadikan sebagai representasi dari ketersediaan sumber daya komputasi dinamis yang dapat dialokasikan dan direalokasikan sesuai dengan permintaan. Mekanisme live migration VM di antara server fisik yang terdapat di dalam data center cloud digunakan untuk mencapai konsolidasi dan memaksimalkan utilisasi VM. Pada prosedur konsoidasi vm, pemilihan dan penempatan VM sering kali menggunakan kriteria tunggal dan statis. Dalam penelitian ini diusulkan pemilihan dan penempatan VM menggunakan multi-criteria decision making (MCDM) pada prosedur konsolidasi VM dinamis di lingkungan cloud data center guna meningkatkan layanan cloud computing. Pendekatan praktis digunakan dalam mengembangkan lingkungan cloud computing berbasis OpenStack Cloud dengan mengintegrasikan VM selection dan VM Placement pada prosedur konsolidasi VM menggunakan OpenStack-Neat. Hasil penelitian menunjukkan bahwa metode pemilihan dan penempatan VM melalui live migration mampu menggantikan kerugian yang disebabkan oleh down-times sebesar 11,994 detik dari waktu responnya. Peningkatan response times terjadi sebesar 6 ms ketika terjadi proses live migration VM dari host asal ke host tujuan. Response times rata-rata setiap vm yang tersebar pada compute node setelah terjadi proses live migration sebesar 67 ms yang menunjukkan keseimbangan beban pada sistem cloud computing.

Virtual Machine Migrating Algorithm Based on Genetic Algorithm in Cloud Data Center

2014 ◽  
Vol 513-517 ◽  
pp. 2031-2034
Author(s):  
Hui Zhang ◽  
Yong Liu
Keyword(s):  
Genetic Algorithm ◽  
Resource Utilization ◽  
Virtual Machine ◽  
Data Center ◽  
Virtual Machines ◽  
Heuristic Algorithms ◽  
Optimal Solution ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Cloud Data

Virtual machine migration is an effective method to improve the resource utilization of cloud data center. The common migration methods use heuristic algorithms to allocation virtual machines, the solution results is easy to fall into local optimal solution. Therefore, an algorithm called Migrating algorithm based on Genetic Algorithm (MGA) is introduced in this paper, which roots from genetic evolution theory to achieve global optimal search in the map of virtual machines to target nodes, and improves the objective function of Genetic Algorithm by setting the resource utilization of virtual machine and target node as an input factor into the calculation process. There is a contrast between MGA, Single Threshold (ST) and Double Threshold (DT) through simulation experiments, the results show that the MGA can effectively reduce migrations times and the number of host machine used.

scholarly journals Virtual CPU Scaling for Efficient Server Power Consumption in Cloud Data Center

2020 ◽  
Vol 3 (2) ◽  
pp. 11-20
Author(s):  
Noora N. Bhaya ◽  
Rabah A. Ahmed
Keyword(s):  
Cloud Computing ◽  
Power Efficiency ◽  
Data Centers ◽  
Power Saving ◽  
Processing Unit ◽  
Cloud Infrastructure ◽  
Financial Benefit ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Central Processing

Cloud computing is a fast-growing technology used by major corporations these days because of the flexibility framework it provides to consumers. Cloud technology requires large data centers consisting of multiple IT equipment and servers. One main problem with these data centers is the vast amount of power consumed during servers operation. This reduces financial benefit and increases the need to produce more energy to cover the needs of operating the cloud infrastructure. This paper proposes an approach for managing the virtual central processing unit (vCPU) of a virtual machine to improve server power efficiency. A framework is used to study the proposed approach while processing different types of workloads widely found in most general-purpose cloud computing applications. Results indicate an improvement in server power saving.

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