Research on the Virtualization Technology in Cloud Computing Environment

2015 ◽  
Vol 21 ◽  
pp. 191-196 ◽  
Author(s):  
Wei Min Ding ◽  
Benjamin Ghansah ◽  
Yan Yan Wu
Keyword(s):  
Cloud Computing ◽  
End User ◽  
Research Directions ◽  
Cloud Computing Environment ◽  
Server Virtualization ◽  
Computing Platform ◽  
Application Deployment ◽  
Cloud Computing Platform ◽  
Time And Energy ◽  
Technology Resources

Virtualization and Cloud computing are two popular research directions in recent times. Today, Virtualization is being used by a growing number of organizations to reduce power consumption, Server Consolidation, Testing and Development, Dynamic Load Balancing and Disaster Recovery, Virtual Desktops and Improved System Reliability and Security. Virtualization also provides high availability for critical applications, and streamlines application deployment and migrations. Through cloud computing, Information Technology resources can be delivered as services over the Internet to the end user. Virtualization is one of such important core technologies of cloud computing. In this paper, we present a detailed review on virtualization. Furthermore, three technologies for x86 CPU virtualization and the architecture of Xen are introduced. Specifically, we propose an architecture of the cloud computing platform based on virtualization. Finally, we discuss the performance evaluation of server virtualization in saving cost, time and energy consumption.

A Trust Model of P2P in Cloud Computing Environment

2013 ◽  
Vol 278-280 ◽  
pp. 1962-1965
Author(s):  
Song Fei ◽  
Xiao Jing Wang ◽  
Zhe Cui
Keyword(s):  
Cloud Computing ◽  
Trust Model ◽  
Computing Environment ◽  
Trust Mechanism ◽  
Cloud Computing Environment ◽  
Computing Platform ◽  
Cloud Computing Service ◽  
Cross Platform ◽  
Cloud Computing Platform ◽  
P2p Technology

Proposed a new trust model based on P2P technology in the cloud computing environment. The model takes into account more than one cloud computing platform, that is, considering the different cloud computing service provider provide the service of a cross-cloud platform. Such cross-platform cloud (Cross Cloud) can be called the composite cloud computing platform or cloud associated cloud computing platform.The nodes in the cloud computing environment are divided into two categories: customers and providers. According to the different roles of these two nodes, we designed a different trust mechanism, to divide the trust domain with independent single cloud, considered node independence and manageability of domain to process trust choice and trust update, and proposed a new kind of cloud computing service - trust recommendation service.

Building Intelligent Virtual Learning Community Based on GAE

2011 ◽  
Vol 403-408 ◽  
pp. 1530-1534 ◽  
Author(s):  
Jun Han ◽  
Hui Bin Yin ◽  
Jing Liu ◽  
Jing Dong
Keyword(s):  
Cloud Computing ◽  
Online Learning ◽  
Learning Community ◽  
Virtual Learning ◽  
Computing Environment ◽  
Community Based ◽  
Virtual Learning Community ◽  
Cloud Computing Environment ◽  
Computing Platform ◽  
Cloud Computing Platform

Virtual learning community has become the main online learning place for learners, and cloud computing provides new tools for the development of virtual learning community. Based on the Google APP Engine (GAE) cloud computing platform provided by Google Company, the article explained the construction of the virtual learning community in cloud computing environment.

Collaborative management and control of blockchain in cloud computing environment

2020 ◽  
pp. 1-11
Author(s):  
Guanghai Tang ◽  
Hui Zeng
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Consensus Algorithm ◽  
Collaborative Management ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
System Load ◽  
Computing Platform ◽  
Cloud Computing Platform ◽  
And Control

Cloud computing, as a product of the fusion and development of computer technology and Internet technology, not only realized the innovation of IT technology but also A major revolution in the IT business model will bring unprecedented and profound changes to the information industry. The main purpose of this article is to study the collaborative management and control method of blockchain in a cloud computing environment. This article mainly uses the blockchain consensus algorithm to analyze and research the blocking technology in the logistics supply chain, and solves the supplier’s benefit formula step by step; also uses the CloudBTF algorithm, Max-min algorithm, FCFS of cloud computing Algorithm, and compare the efficiency and security of the three methods to get the most conducive to the collaborative management and control of the blockchain. The experimental results of this paper show that blockchain collaborative management in a cloud computing environment can greatly improve the security of massive data storage and the collaborative distribution of data. Among them, the use of cloud computing platform priority algorithms can improve system load balancing by up to 12%, while Using the cloud computing platform FCFS algorithm can improve system load balancing by up to 15%.

Power Management of Virtualized Cloud Computing Platform

2012 ◽  
Vol 35 (6) ◽  
pp. 1262 ◽  
Author(s):  
Ke-Jiang YE ◽  
Zhao-Hui WU ◽  
Xiao-Hong JIANG ◽  
Qin-Ming HE
Keyword(s):  
Cloud Computing ◽  
Power Management ◽  
Computing Platform ◽  
Cloud Computing Platform

Predicting Node Failures in an Ultra-Large-Scale Cloud Computing Platform

2020 ◽  
Vol 29 (2) ◽  
pp. 1-24
Author(s):  
Yangguang Li ◽  
Zhen Ming (Jack) Jiang ◽  
Heng Li ◽  
Ahmed E. Hassan ◽  
Cheng He ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Computing Platform ◽  
Cloud Computing Platform ◽  
Node Failures

In defense of decentralized research data management

Neuroforum ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Michael Hanke ◽  
Franco Pestilli ◽  
Adina S. Wagner ◽  
Christopher J. Markiewicz ◽  
Jean-Baptiste Poline ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Management ◽  
Research Data ◽  
Data Archive ◽  
Individual Scientist ◽  
Computing Platform ◽  
Research Data Management ◽  
Cloud Computing Platform ◽  
Research Objects ◽  
Central Services

Abstract Decentralized research data management (dRDM) systems handle digital research objects across participating nodes without critically relying on central services. We present four perspectives in defense of dRDM, illustrating that, in contrast to centralized or federated research data management solutions, a dRDM system based on heterogeneous but interoperable components can offer a sustainable, resilient, inclusive, and adaptive infrastructure for scientific stakeholders: An individual scientist or laboratory, a research institute, a domain data archive or cloud computing platform, and a collaborative multisite consortium. All perspectives share the use of a common, self-contained, portable data structure as an abstraction from current technology and service choices. In conjunction, the four perspectives review how varying requirements of independent scientific stakeholders can be addressed by a scalable, uniform dRDM solution and present a working system as an exemplary implementation.

Sign in / Sign up

Export Citation Format

Share Document