scholarly journals A Review on Different Types of Live VM Migration Methods with Proposed Pre-Copy Approach

2018 ◽  
Vol 7 (4.12) ◽  
pp. 6
Author(s):  
Arvind Kumar Bhatia ◽  
Gursharan Singh
Keyword(s):  
Virtual Machine ◽  
Virtual Machines ◽  
Virtual Machine Migration ◽  
Server Virtualization ◽  
Physical Machine ◽  
Dynamic Movement ◽  
State Transfer ◽  
Different Types ◽  
Migration Method ◽  
Memory Content

Cloud computing is being considered as the future architecture of IT world. Virtualization creates logical resources from physical resources which are allocated with flexibility to applications. Server virtualization is a technique for the division of the physical machine into many Virtual Machines; every Virtual Machine has the capacity of applications execution similar to physical machine. The capability of Virtual Machine migration i.e. dynamic movement of Virtual Machines between physical machines is achieved by virtualization. Migration techniques differ w.r.t order of state transfer. Pre-copy migration method transfers all pages of memory from source to destination while Virtual Machine is executing on source. Post-copy migration is transfer of memory. content after the transfer of process state. Specially, post-copy migration, first copied the process states to the destination machine. Total time of migration, Total pages transferred and Downtime are important parameters considered during live Virtual Machine migration. Many improved live pre copy Virtual Machine migration techniques tries to decrease all the three above mentioned parameters. Proposed approach also tries to minimize all the three performance parameters.  

A Load Balancing Policy for Virtual Desktop Service

2012 ◽  
Vol 263-266 ◽  
pp. 1564-1567
Author(s):  
Sung Hoon Son
Keyword(s):  
Load Balancing ◽  
Virtual Machine ◽  
Load Balance ◽  
Large Scale ◽  
Virtual Machines ◽  
Migration Policy ◽  
Virtual Machine Migration ◽  
Physical Machine ◽  
Virtual Desktop

In this paper, a virtual machine migration policy for large scale virtual desktop service is proposed. Usually a virtual desktop service is composed of several physical machines, each of which is running several virtual machines. Sometimes virtual machine should be relocated to other physical machine when load balance over the system lost. In this situation, a management server must answer two questions: who should be relocated and where is the destination host? The proposed migration policy in this paper is three kinds. We suggest the best policy from the viewpoint of user and system. By experiments, we show that our policy reduce user connect time and increase the number of concurrent virtual machines.

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

Live Migration for Virtual Machine Based on Kalman Prediction of Dirty Pages

2014 ◽  
Vol 668-669 ◽  
pp. 1363-1367 ◽  
Author(s):  
Zhi Hong Sun ◽  
Xian Lang Hu
Keyword(s):  
Virtual Machine ◽  
Migration Time ◽  
Live Migration ◽  
Virtual Machine Migration ◽  
Memory State ◽  
Dynamic Memory ◽  
Virtual Machine Live Migration ◽  
Migration Method ◽  
Kalman Prediction ◽  
Total Migration

The live migration of virtual machine (VM) is an important technology of cloud computing. Down-time, total migration time and network traffic data are the key measures of performance. Through the analysis of dynamic memory state of a virtual machine migration process, we propose a dirty pages algorithm prediction based on pre-copy to avoid dirty pages re transmission. Experimental results show that, compared with the Xen virtual machine live migration method adopted, our method can at least reduce 15.1% of the total amount of data and 12.2% of the total migration time.

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.

scholarly journals A Virtual Machine Migration Strategy Based on the Relevance of Services against Side-Channel Attacks

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Ji-Ming Chen ◽  
Shi Chen ◽  
Xiang Wang ◽  
Lin Lin ◽  
Li Wang
Keyword(s):  
Internet Of Things ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Edge Computing ◽  
Security And Privacy ◽  
Side Channel ◽  
Virtual Machine Migration ◽  
Side Channel Attacks ◽  
Migration Strategy ◽  
Vm Migration

With the rapid development of Internet of Things technology, a large amount of user information needs to be uploaded to the cloud server for computing and storage. Side-channel attacks steal the private information of other virtual machines by coresident virtual machines to bring huge security threats to edge computing. Virtual machine migration technology is currently the main way to defend against side-channel attacks. VM migration can effectively prevent attackers from realizing coresident virtual machines, thereby ensuring data security and privacy protection of edge computing based on the Internet of Things. This paper considers the relevance between application services and proposes a VM migration strategy based on service correlation. This strategy defines service relevance factors to quantify the degree of service relevance, build VM migration groups through service relevance factors, and effectively reduce communication overhead between servers during migration, design and implement the VM memory migration based on the post-copy method, effectively reduce the occurrence of page fault interruption, and improve the efficiency of VM migration.

scholarly journals A Decentralized Virtual Machine Migration Approach of Data Centers for Cloud Computing

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaoying Wang ◽  
Xiaojing Liu ◽  
Lihua Fan ◽  
Xuhan Jia
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Large Scale ◽  
Data Centers ◽  
Virtual Machines ◽  
Quality Of Services ◽  
Virtual Machine Migration ◽  
Power Models ◽  
Key Steps

As cloud computing offers services to lots of users worldwide, pervasive applications from customers are hosted by large-scale data centers. Upon such platforms, virtualization technology is employed to multiplex the underlying physical resources. Since the incoming loads of different application vary significantly, it is important and critical to manage the placement and resource allocation schemes of the virtual machines (VMs) in order to guarantee the quality of services. In this paper, we propose a decentralized virtual machine migration approach inside the data centers for cloud computing environments. The system models and power models are defined and described first. Then, we present the key steps of the decentralized mechanism, including the establishment of load vectors, load information collection, VM selection, and destination determination. A two-threshold decentralized migration algorithm is implemented to further save the energy consumption as well as keeping the quality of services. By examining the effect of our approach by performance evaluation experiments, the thresholds and other factors are analyzed and discussed. The results illustrate that the proposed approach can efficiently balance the loads across different physical nodes and also can lead to less power consumption of the entire system holistically.

Virtual Machine Migration Based on Trust Measurement of Computer Node

2014 ◽  
Vol 536-537 ◽  
pp. 678-682
Author(s):  
Zhi Hong Liang ◽  
Zhi Qiang Liang ◽  
Yi Ming Tan ◽  
Xue Cheng Lv
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Virtual Machine Migration ◽  
Performance Constraints ◽  
Computing Platform ◽  
Physical Machine ◽  
Cloud Computing Platform ◽  
Trust Measurement ◽  
Computer Node

Currently, the study of virtual machine migration in cloud computing platform which usually did not consider the trustworthiness of target physical machine. For this, the paper proposes a trusted virtual machine migration with performance constraints algorithm (TVM2PC). The trustworthiness of target physical machine includes direct trustworthiness and indirect trustworthiness. By this method, a virtual machine will be migrated to a trusted physical machine. A large of experiment shows that the proposed method can give a better result than the existing method in load balancing and trustworthiness.

scholarly journals A Virtual Machine Migration Strategy Based on Time Series Workload Prediction Using Cloud Model

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Yanbing Liu ◽  
Bo Gong ◽  
Congcong Xing ◽  
Yi Jian
Keyword(s):  
Time Series ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Cloud Model ◽  
Prediction Algorithm ◽  
Virtual Machine Migration ◽  
Migration Strategy ◽  
Workload Prediction ◽  
Vm Migration ◽  
Host Machine

Aimed at resolving the issues of the imbalance of resources and workloads at data centers and the overhead together with the high cost of virtual machine (VM) migrations, this paper proposes a new VM migration strategy which is based on the cloud model time series workload prediction algorithm. By setting the upper and lower workload bounds for host machines, forecasting the tendency of their subsequent workloads by creating a workload time series using the cloud model, and stipulating a general VM migration criterion workload-aware migration (WAM), the proposed strategy selects a source host machine, a destination host machine, and a VM on the source host machine carrying out the task of the VM migration. Experimental results and analyses show, through comparison with other peer research works, that the proposed method can effectively avoid VM migrations caused by momentary peak workload values, significantly lower the number of VM migrations, and dynamically reach and maintain a resource and workload balance for virtual machines promoting an improved utilization of resources in the entire data center.

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 Low Power Consumption on Cloud Data Centers Using HSA Algorithm

2020 ◽  
pp. 78-84
Author(s):  
Louay Al Nuaimy ◽  
Tadele Debisa Deressa ◽  
Mohammad Mastan ◽  
Syed Umar
Keyword(s):  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Search Algorithm ◽  
Rapid Development ◽  
Electricity Consumption ◽  
Cloud Infrastructure ◽  
Virtual Machine Migration ◽  
Cloud Data ◽  
The Right

The rapid development of knowledge and communication has created a new processing style called cloud computing. One of the key issues facing cloud infrastructure providers is minimizing costs and maximizing profitability. Power management in cloud centres is very important to achieve this. Energy consumption can be reduced by releasing inactive nodes or by reducing the migration of virtual machines. The second is one of the challenges of choosing the virtual machine deployment method to migrate to the right node. This article proposes an approach to reduce electricity consumption in cloud centres. This approach adapts Harmony's search algorithm to move virtual machines. Positioning is done by sorting nodes and virtual machines according to their priorities in descending order. Priority is calculated based on the workload. The proposed procedure is envisaged. The evaluation results show less virtual machine migration, greater efficiency and lower energy consumption.

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