Comparative study of application performance on virtual machine and physical machine

2012 ◽  
Author(s):  
M R Anala ◽  
G Shobha
Keyword(s):  
Comparative Study ◽  
Virtual Machine ◽  
Application Performance ◽  
Physical Machine

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.

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