The Design and Analysis of Cloud Computing Information Management

2014 ◽  
Vol 556-562 ◽  
pp. 5855-5858
Author(s):  
Ya Ni Zhang
Keyword(s):  
Cloud Computing ◽  
Management Information System ◽  
Control Mechanism ◽  
Design Method ◽  
Dynamic Control ◽  
Management Information ◽  
Computing Platform ◽  
Application Systems ◽  
Time Period ◽  
Cloud Computing Platform

At present, the application systems most enterprises have are self-built and only used in inner-enterprise, thus information can’t be shared efficiently and up-front cost and ongoing maintenance costs are high. To solve this problem, this paper presents a design method of management information system based on cloud computing, which take full advantage of cloud computing platform: HDFS-based cloud-computing copy replication dynamic control mechanism. It can determine whether to increase or decrease the number of copies by reading the number of requests at the same time period and select the appropriate node to add or remove files copies according to historical information so as to achieve the purpose of improving the efficiency of concurrent reads.

Research of Cloud Computing in Management Information System

2013 ◽  
Vol 655-657 ◽  
pp. 1826-1829
Author(s):  
Zheng Xing Xiao
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
Management Information System ◽  
Massive Data ◽  
Management Information ◽  
Computing Platform ◽  
Complex Functions ◽  
Cloud Computing Platform ◽  
Diverse Data

characteristics of current MIS System are massive data、diverse data and complex functions. This kind of System requires higher requirement to Storage and Computing. This paper proposes a way to resolve it by build cloud computing platform by making full use of large number of idle computers.

The Research on Knowledge Sharing in the Small and Medium-Sized Enterprise Based on Cloud Computing

2014 ◽  
Vol 686 ◽  
pp. 736-741
Author(s):  
Ji Chao Hu ◽  
Xiang Wen Yang
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
Knowledge Management ◽  
Management Information System ◽  
Management System ◽  
Information Management System ◽  
Enterprise Management ◽  
Management Information ◽  
Enterprise Information ◽  
Computing Platform

The paper combine cloud computing with knowledge management, and classify the knowledge management of enterprise information management system, finally the paper plan and design the overall architecture of enterprise management information system. According to the model of cloud computing, establish the cloud computing platform based on the construction of cloud computing and virtualization technology, in order to achieve the overall architecture of the management information system of enterprise that migrate to the cloud computing environment. This paper mainly introduced in the cloud computing architecture of enterprise management information system under the environment of cloud computing and implementation of knowledge management system.

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.

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