Efficient Migration of Virtual Machines between Public and Private Cloud

Author(s):  
Chun-Hui Suen ◽  
Markus Kirchberg ◽  
Bu Sung Lee
2020 ◽  
Vol 12 (0) ◽  
pp. 1-5 ◽  
Author(s):  
Narūnas Kapočius

Containerisation and microservices architecture are getting momentum in nowadays ICT field. Containers are deployed in both public and private cloud environments and usually for flexibility purposes are deployed in VM (Virtual Machines) environment. Microservices have a demand on a high number of containers which requires orchestration and Kubernetes is one of the most popular choice. However, Kubernetes does not offer networking solution and it is provided by CNI (Container Networking Interface) and its’ plugins. In order to choose best plugin their performance needs to be evaluated. In this paper nine most popular CNI plugins TCP and HTTP protocols performance is evaluated in virtualised VMware ESXi and physical data centre environment. The results help to choose which CNI plugins to use either in virtualised or physical data centre environment.


Author(s):  
Marta Štimec ◽  
Matija Cankar

With the growing adoption of using virtual machines over physical hosts as a form of resource consolidation, The English-Slovene Glossary of Virtualization-related Terms encompassing management of virtual machines, cloud orchestration and data storage seemed like the next logical step.The Glossary of Virtualization-related Terms has been translated into Slovene and reviewed by experts in the fields of cloud computing, virtualization technologies and linguists. Close to 6000 terms had been localized for the Slovene market, using the advanced version of Poedit application – the editor for translating apps and websites. PoEdit automatically displays translation equivalents either from its own base (built-in translation memory) or from the base of previously translated words and phrases, which had been created and offered as opensource by other users. Based on these, it makes suggestions and, over time, learns enough to fill in frequently used strings. The translated text was then imported into its original page location – the Graphic User Interface (visible on buttons on the dashboard) of the customized ManageIQ Enterprise Virtualization Manager (EVM) software used by administrators of public and private clouds. Hence the main criterion was brevity and precision in transfering meaning across languages. This is where we encountered most problems – neologisms and existing words that acquire new meaning as a result of rapid development of virtualization technology. To avoid merely adding a suffix while the core of the word remains the same in Slovene (e.g. tenant, tenant-ov) and also to encourage further additions, comments or suggested changes the glossary has been made available on Wikipedia, the online encyclopedia.


Author(s):  
Adib Habbal ◽  
Siti Aminah Abdullah ◽  
Emmanuel O.C. Mkpojiogu ◽  
Suhaidi Hassan ◽  
Nabil Benamar

Cloud computing has attracted the attention of educational and research institutions as a way to support modern trends in teaching and learning. This article describes the performance assessment of a private cloud within a university environment using the Web of System Performance (WOSP) model. A survey was carried out to measure the respondents' attitude towards the use of private cloud in which students and experts serve as sample. Testing was conducted by designing a virtual lab consisting of a number of virtual machines operated by a selected sample. The results showed that the usage of cloud computing in university has good perceived system performance judging from how it fares in the constituent parts of the WOSP model. Furthermore, the study revealed that usability and flexibility outperformed criterion like security. Moreover, several non-functional criteria outperformed functionality. In short, the knowledge and results presented from assessing a private cloud using WOSP model could be beneficial for users, designers and managers of private clouds especially in universities.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Shyamala Loganathan ◽  
Saswati Mukherjee

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.


2015 ◽  
Vol 7 (2) ◽  
pp. 117-132
Author(s):  
Stanislaw Lota ◽  
Marcin Markowski

Abstract Virtualization of physical network devices is a relatively new technology, that allows to improve the network organization and gives new possibilities for Software Defined Networking (SDN). Network virtualization is also commonly used for testing and debugging environments, before implementing new designs in production networks. Important aspect of network virtualization is selecting virtual platform and technology, that offer maximal performance with minimal physical resource utilization. This article presents a comparative analysis of performance of the virtual network created by the virtual CSR1000v and virtual machines running Windows 8.1 on two different virtual private cloud platforms: VMware vSphere 5.5 and Microsoft Hyper-V Server 2012 R2. In such prepared testbed we study the response time (delay) and throughput of virtual network devices.


2015 ◽  
Vol 24 (08) ◽  
pp. 1550111 ◽  
Author(s):  
Chunlin Li ◽  
LaYuan Li

The paper proposes hierarchical scheduling optimization scheme in hybrid cloud. Our proposed hierarchical scheduling takes advantage of the interaction of cloud users, private cloud and public cloud. For high level optimization in hybrid cloud, the objective of public cloud provider optimization is to maximize the revenue of providing virtual machines (VMs) and minimize the energy cost. The private cloud users' applications give the unique optimal payment to public cloud providers under deadline and cost constraint to maximize the satisfaction of private cloud user applications. The objective of low-level scheduling optimization is to minimize the cost and execution time of private cloud application. From the simulation results, the revenue, execution success ratio and resource utilization of our proposed hierarchical scheduling algorithm are better than other related works.


2017 ◽  
Vol 5 (4RACSIT) ◽  
pp. 76-80
Author(s):  
Madhumala R B ◽  
Harshavardhan Tiwari

The new developments in the field of information technology offered the people enjoyment, comforts and convenience. Cloud computing is one of the latest developments in the IT industry also known as on-demand computing. It provides the full scalability, reliability, high performance and relatively low cost feasible solution as compared to dedicated infrastructures. It is the application provided in the form of service over the internet and system hardware in the data centers that gives these services. This technology has the capacity to admittance a common collection of resources on request. It is proving extremely striking to cash-strapped IT departments that are wanted to deliver better services under pressure. When this cloud is made available for the general customer on pay per use basis, then it is called public cloud. When customer develops their own applications and run their own internal infrastructure then is called private cloud. Integration and consolidation of public and private cloud is called hybrid cloud.


2020 ◽  
Vol 1 (2) ◽  
pp. 39-46
Author(s):  
Arpita Shah ◽  
Narendra Patel

Of late Multitenant model with In-Memory database has become prominent area for research. The paper has used advantages of multitenancy to reduce the cost for hardware, labor and make availability of storage by sharing database memory and file execution. The purpose of this paper is to give overview of proposed Supple architecture for implementing in-memory database backend and multitenancy, applicable in public and private cloud settings. Backend in-memory database uses column-oriented approach with dictionary based compression technique. We used dedicated sample benchmark for the workload processing and also adopt the SLA penalty model. In particular, we present two approximation algorithms, Multi-tenant placement (MTP) and Best-fit Greedy to show the quality of tenant placement. The experimental results show that Multi-tenant placement (MTP) algorithm is scalable and efficient in comparison with Best-fit Greedy Algorithm over proposed architecture.


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