Design and Realization of the Cloud Data Backup System Based on HDFS

Author(s):  
Dong Guo ◽  
Yong Du ◽  
Qiang Li ◽  
Liang Hu
Keyword(s):  
Author(s):  
Sung Woon Kang ◽  
Ho Min Jung ◽  
Jung Geun Lee ◽  
Jin Haeng Cho ◽  
Young Woong Ko
Keyword(s):  

Author(s):  
A.M. Patutina ◽  
I.V. Rudakov

The paper considers the method of researching the fault tolerance of the backup system based on semi-Markov processes, and presents a quick overview of calculation methods for dynamic and static models of reliability analysis. The research shows that implementations based on semi-Markov processes have practically no limitations on building failure, recovery and backup models, and also provide the most accurate results. We described the existing storage technologies. By mixed, i.e., analytical-simulation, modeling, we implemented the data backup model. The simulation part, which determines the fault tolerance of switches and servers, is presented in terms of queuing theory, and the analytical part suggests defining fault tolerance for a data storage system based on semi-Markov processes.


Author(s):  
Wei Zhang ◽  
Daniel Agun ◽  
Tao Yang ◽  
Rich Wolski ◽  
Hong Tang
Keyword(s):  

Author(s):  
Yang Chao ◽  
Xu Wen ◽  
Wu Guohui ◽  
Qi Xinge ◽  
Liu Sai ◽  
...  
Keyword(s):  

2021 ◽  
Vol 2030 (1) ◽  
pp. 012061
Author(s):  
Shibin Hu ◽  
Yiyong Lin ◽  
Zhang Qi ◽  
Qiang Fu ◽  
Jianbiao Chen

2020 ◽  
Vol 42 ◽  
pp. e46073
Author(s):  
Leandro Duarte Pereira ◽  
Pedro Paulo Balestrassi ◽  
Vinicius de Carvalho Paes ◽  
Anderson Paulo de Paiva ◽  
Rogério Santana Peruchi ◽  
...  

The Information and Communication Technology (ICT) becomes a critical area to business success; organizations need to adopt additional measures to ensure the availability of their services. However, such services are often not planned, analyzed and monitored, which impacts the assurance quality to customers. The backup is the service addressed in this study, with the object of study of the automated data backup systems in operation at the Federal University of Itajuba - Brazil. The main objective of this research was to present a logical sequence of steps to obtain short-term forecast models that estimate the point at which each recording media reaches its storage capacity limit. The input data was collected in the metadata generated by the backup system, with 2 years data window. For the implementation of the models, the simple univariate linear regression technique was employed in conjunction, in some cases, with the simple segmented linear regression. In order to discover the breakpoint, a targeted approach to residual analysis was applied. The results obtained by the iterative implementation of the proposed algorithm showed adherence to the characteristics of the analyzed series, with accuracy measures, regression significance, normality residual through control charts, model adjustment, among others. As a result, an algorithm was developed for integration into automated backup systems using the methodology described in this study.


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