Energy efficient quality of service aware virtual machine migration in cloud computing

2018 ◽  
Author(s):  
Neeraj Kumar Sharma ◽  
Priyanka Sharma ◽  
Ram Mohana Reddy Guddeti
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Virtual Machine ◽  
Energy Efficient ◽  
Virtual Machine 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.

scholarly journals Priority-Based Virtual Machine Selection Algorithm in Cloud Computing

2019 ◽  
Vol 8 (3) ◽  
pp. 1457-1462
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Cloud Service Provider

Cloud computing technology has gained the attention of researchers in recent years. Almost every application is using cloud computing in one way or another. Virtualization allows running many virtual machines on a single physical computer by sharing its resources. Users can store their data on datacenter and run their applications from anywhere using the internet and pay as per service level agreement documents accordingly. It leads to an increase in demand for cloud services and may decrease the quality of service. This paper presents a priority-based selection of virtual machines by cloud service provider. The virtual machines in the cloud datacenter are configured as Amazon EC2 and algorithm is simulated in cloud-sim simulator. The results justify that proposed priority-based virtual machine algorithm shortens the makespan, by 11.43 % and 5.81 %, average waiting time by 28.80 % and 24.50%, and cost of using the virtual machine by 21.24% and 11.54% as compared to FCFS and ACO respectively, hence improving quality of service.

scholarly journals Energy Efficient VM Migration in Cloud Datacenter using Dolphin Echolocation Optimization with Tchebycheff Algorithm

2019 ◽  
Vol 8 (2) ◽  
pp. 86-94 ◽  
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Energy Efficient ◽  
System Performance ◽  
Migration Process ◽  
Virtual Machine Migration ◽  
Vm Migration ◽  
Multi Objective ◽  
Cloud Datacenter ◽  
Single Objective

The workload in cloud computing surroundings changes progressively delivering unwanted circumstances, for example, load unbalancing and minor usage. Virtual machine migration is an impressive plan in such circumstances inorder to improve system performance. With a specific end goal to give productive energy virtual machine migration is essential that migrates a running virtual machine without disconnecting the client or application. In any case, an algorithm in view of a single objective is generally familiar with to coordinate the migration process. Unexpectedly, there stay alive unconsidered variables affecting the migration process, for example, burden capacity, power utilization and resource wastage. We offer a multi-objective algorithm for obtaining VM migration by evaluating the multi objectives that are responsible for migration overhead. In this manner, we suggest a narrative relocation approach united by a Multi objective Dolphin Echolocation Optimization Algorithm (MO-DEOA) to assess several objectives. The aim is to efficiently obtain improved migration that concurrently diminishes power consumption by guaranteeing the performance of the system.

scholarly journals Improving Quality-of-Service in Cloud/Fog Computing through Efficient Resource Allocation

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1267 ◽  
Author(s):  
Samson Akintoye ◽  
Antoine Bagula
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Virtual Machine ◽  
Task Allocation ◽  
Optimization Problems ◽  
Fog Computing ◽  
Virtual Machine Placement ◽  
Computing Environment ◽  
Virtual Resources

Recently, a massive migration of enterprise applications to the cloud has been recorded in the IT world. One of the challenges of cloud computing is Quality-of-Service management, which includes the adoption of appropriate methods for allocating cloud-user applications to virtual resources, and virtual resources to the physical resources. The effective allocation of resources in cloud data centers is also one of the vital optimization problems in cloud computing, particularly when the cloud service infrastructures are built by lightweight computing devices. In this paper, we formulate and present the task allocation and virtual machine placement problems in a single cloud/fog computing environment, and propose a task allocation algorithmic solution and a Genetic Algorithm Based Virtual Machine Placement as solutions for the task allocation and virtual machine placement problem models. Finally, the experiments are carried out and the results show that the proposed solutions improve Quality-of-Service in the cloud/fog computing environment in terms of the allocation cost.

scholarly journals Enhancing Virtual Machine Live Migration Time Using Vcpu Limits

2018 ◽  
Vol 7 (4.16) ◽  
pp. 28-31
Author(s):  
Aula Abdel Latief Dewan ◽  
Rabah Abood Ahmed
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Virtual Machine ◽  
Data Centers ◽  
Migration Time ◽  
Live Migration ◽  
Important Method ◽  
Virtual Machine Live Migration ◽  
Computing Platforms

In the Cloud Computing, the live migration of a virtual machine or VM from one physical machine to another is a vital process applied on the service provider side. Live migration helps administrators manage data centers resources optimally. Due to the intensive daily use, it is necessary to improve the performance of VM migration-this is reflected in improving the quality of service provided to the customer while minimizing the costs incurred. Pre-copy is an important method of live migration that has been adopted in many cloud computing platforms. One main drawback of this method is the degradation of its performance when the migrating VM runs one or more of the processes that write on the memory pages faster than the speed of transferring those pages. This makes migration time-consuming. In this paper, we propose an approach to address this issue by reducing the generation rate of the modified pages while maintaining the service provided to the customer. This approach was applied to the real Xen platform and the results showed an improvement in the time of live migration of the virtual machine that runs an intensive write process up to 40% compared to the migration time of the original Xen platform.  

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