scholarly journals The Method Balance Consistency Availability on Systems Virtual Machine

2019 ◽  
Vol 8 (12S) ◽  
pp. 802-805
Keyword(s):  
Virtual Machine ◽  
Distributed Storage ◽  
Original Study ◽  
Physical Machine ◽  
Effective Activity ◽  
Information Consistency

In this time, a few associations are putting away their information on distributed storage so as to meet the prerequisites of effective activity like soundness, versatility, and accessibility of administrations. Information replication benefits in distributed storage frameworks are there to improve execution. In this unique situation, the prerequisites for guaranteeing information consistency have turned out to be progressively significant. In this paper, we have proposed a virtual server solution for refreshing replication, effectively settling assets, distinguishing and avoiding gridlocks at the server sides. In this original study, we have demonstrated that the proposed arrangement yields the outcomes for the construction which guarantees information consistency in regard to expenses and idleness. we utilize the Open Stack apparatus, which joins a proposed calculation on Adjusting Consistency Accessibility in Physical Machine for keeping up information consistency in Distributed storage Frameworks.

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.

Reasoning Based Virtual Machine Mapping Toward Physical Machine

2019 ◽  
pp. 1-12
Author(s):  
Adeel Aslam ◽  
Hanhua Chen ◽  
Jiang Xiao ◽  
Song Wu ◽  
Hai Jin
Keyword(s):  
Virtual Machine ◽  
Physical Machine

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 Securing SAAS service under cloud computing based multi-tenancy systems

2019 ◽  
Vol 13 (1) ◽  
pp. 65
Author(s):  
Trinathbasu Miriyala ◽  
JKR Sastry
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Efficient Method ◽  
Service Provider ◽  
Virtual Machines ◽  
Cloud Service ◽  
Cloud Service Provider ◽  
Physical Machine ◽  
Multiple Users ◽  
Business Requirements

<p><span lang="EN-US">Cloud computing technologies are being used by many who need computing resources such as software, platform and infrastructure as per their business requirements in terms of provisioning and pay for the usage as per actual consumption of the services based on the SLA signed by the user and cloud service provider. Software running on a physical machine is being provided as services to the end users. For the reasons of cost economies access to software that uses a database is being provided to multiple users. The access to the software is provided either directly or through a virtual machine. The software being provided as service uses the same database for many of the users who have requisitioned for the same. As a result, there could be encroachments by the users into the data of others. There is a need to secure the data belonging to several users while all of them access the data using the same application. In this paper an efficient method is presented for securing the data processed by software which is offered as a service to multiple users either directly or through virtual machines.    </span></p>

scholarly journals Strategi Efisiensi Energi dan Penyeimbangan Beban Kerja Layanan Cloud Computing Melalui Konsolidasi Mesin Virtual Dinamis

2020 ◽  
Vol 3 (1) ◽  
pp. 1-12
Author(s):  
Abdullah Fadil
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Data Center ◽  
Vm Migration ◽  
Physical Machine

Arsitektur data center di dalam cloud computing merupakan lingkungan yang heterogen dan terdistribusi, tersusun atas gugusan jaringan physical machine (PM) atau server dengan berbagai kapasitas sumber daya komputasi yang berbeda-beda di dalam PMnya. Kondisi permintaan (demand) dan ketersediaan (supply) pada layanan cloud yang fluktuatif tersebut membuat data center cloud harus dibuat elastis. Virtual Machine (VM) merupakan representasi dari ketersediaan sumber daya komputasi dinamis yang dapat dialokasikan dan direlokasikan sesuai dengan permintaan. VM yang berada di dalam data center cloud dapat dipindahkan dari satu PM ke PM lainnya menggunakan migrasi VM secara langsung (live VM migration) ataupun tidak langsung (off-line VM migration). lingkungan cloud computing yang dinamis dan terdistribusi mengharuskan strategi pengambilan keputusan di dalam konsolidasi VM harus dibuat sedinamis mungkin atau bahkan adaptif dengan mempertimbangkan heterogenitas sumber daya virtual sesuai dengan layanan cloud computing yang disajikan. Sehingga, dalam penelitian ini diusulkan efisiensi energi sekaligus menjaga kinerja layanan cloud computing melalui penyeimbangan beban kerja dengan teknik migrasi VM yang terdapat pada prosedur konsolidasi VM dinamis. Strategi pengambilan keputusan pada prosedur konsolidasi virtual machine dinamis yang diusulkan, dapat meningkatkan kinerja layanan cloud computing sekaligus beban kerja physical machine menjadi seimbang karena keputusan pemilihan VM dan penempatan VM pada physical machine dipilih secara optimal melalui MADM. Konsumsi energi dari physical machine juga dapat di hemat dengan mematikannya karena statusnya idle.

A Practical Approach on Virtual Machine Live Migration

2015 ◽  
pp. 464-483
Author(s):  
Prashanta Kumar Das
Keyword(s):  
Virtual Machine ◽  
Operating Systems ◽  
Live Migration ◽  
Virtual Machine Migration ◽  
The Third ◽  
Physical Machine ◽  
Virtual Machine Live Migration ◽  
Key Features ◽  
Server Maintenance ◽  
Resource Consolidation

Virtualization technology enables organizations to take the benefit of different services, operating systems, and software without increasing their IT infrastructure liabilities. Live migration of virtual machine is the key features of the virtualization. It allows the administrator to move the virtual machine from one physical machine to another physical machine without any interruption. This technique is widely used for load balancing, server maintenance, and resource consolidation. The virtual machine migration problem consists of four distinct steps. The first step is to select the host from where VM migrated. After selecting, the host next step is to select the VM, which is migrated. The third step is to select the host where the migrated VM will be placed, and the last step is to decide the method, which is used to transfer the VM. This chapter covers all the basic information related to VM migration.

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.

Virtual Machine Placement in Cloud Computing: Challenges, Research Gaps, and Future

2021 ◽  
pp. 64-71
Author(s):  
Puneet Kaushal ◽  
◽  
Subash Chander ◽  
Vijay Kumar Sinha ◽  
◽  
...  
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Resource Utilization ◽  
Virtual Machine ◽  
Optimization Methods ◽  
Virtual Machine Placement ◽  
Cloud Environment ◽  
Research Gaps ◽  
Physical Machine ◽  
Main Motive

Cloud computing provides various types of services to users. The goal of virtual machine placement (VMP) is to map the best physical machine to a virtual machine. With the help of Virtual Machine Placement, we can reduce cost, maximize resource utilization, reduced energy consumption of data centers in cloud environments. The focus of Virtual Machine Placement is to saving of power, quality of service. In this paper, we have reviewed various placements techniques used in cloud computing. At last, we have also studied various challenges for virtual machine placement in cloud computing. The main motive of various types of Virtual Machine Placement algorithms have to reduced energy consumption and minimize cost by maximizing utilization of various resources in the cloud platform. For further study, the researcher should focus on these challenges for the best virtual machine placement in a cloud environment. In this paper, we critically examine the techniques, challenges, and research gaps in virtual placements in cotext with Cloud Computing. Cloud computing, placement of virtual machines becomes major problems. For finding the solution to the problem we can use the various virtual machine placement algorithms. The main motive is to reduce consumption of energy, maximum resource utilization, minimizing cost factors used for virtual to the physical machine mapping in the cloud environment. For selecting the best algorithm various optimization methods are used. With these different optimization methods, we can analyze different algorithms. There is a great scope of improvement in existing systems of virtual placements to make them more energy-efficient, more reliable, and fault-tolerant. Redundancy in cloud downloading can be made more intelligent and minimized for duplicate data while downloading and uploading.

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