Open AccessDate Hierarchical Storage Strategy for Data Disaster Recovery
Author(s) -
Tian Jun-Feng,
Zhang Jia-Yao,
Du Rui-Zhong
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2862468
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Cloud storage has become a widely accepted data storage model in recent years. With the development of cloud storage applications in various fields, cloud storage security issues have aroused people's special attention. In this paper, taking aim at ensuring data reliability and satisfying QoS requirements for different users, a method named hierarchical storage-based data disaster recovery strategy was proposed. Cloud computing fault tolerance model is constructed by grading the storage resources of cloud service providers according to the service level to meet the different QoS requirements of the cloud users. On this basis, some storage levels are classified to improve resource utilization. The correctness of the classification strategy is analyzed theoretically, finally, the effectiveness of the proposed strategy is validated by emulation experiment. This paper has the theoretical and practical value to improve the overall experience of users.
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