An Innovative Encryption Method for Agriculture Intelligent Information System based on Cloud Computing Platform

2014 ◽  
Vol 9 (1) ◽  
Author(s):  
Wenxue Tan ◽  
Chunjiang Zhao ◽  
Huarui Wu ◽  
Xiping Wang
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
Computing Platform ◽  
Cloud Computing Platform ◽  
Intelligent Information ◽  
Encryption Method

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.

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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