Issue |
ITM Web Conf.
Volume 12, 2017
The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|
|
---|---|---|
Article Number | 05003 | |
Number of page(s) | 7 | |
Section | Session 5: Information Processing Methods and Techniques | |
DOI | https://doi.org/10.1051/itmconf/20171205003 | |
Published online | 05 September 2017 |
A Reliable and Efficient Data Migration Method Based On GlusterFS
Computer Science, National University of Defense Technology, Changsha, China
dylan-lili@foxmail.com
jack_nudt@163.com
taowang.2005@outlook.com
Big data storage and high speed data access have become the main performance bottleneck for many big data applications. The higher speed data access and lower cost for storage must be required than some applications having small-scale data. Distributed hierarchical storage provides a good storage way to speed data access and lower cost. But it a data migration method which you choose decide the performance of distributed hierarchical storage system because data migration occurs frequently in hierarchical storage systems. There are many data migration methods, which most of those cannot ensure data utterly integrity after data migration. In this paper, we invent a reliable and efficient data migration method to ensure the utterly integrity of migrated data by MD5 checksum and improve performance of data migration by the pipeline technology. Through adjusting parameters, we get the best performance of data migration by using pipeline in our storage system which is a hierarchical storage system based on GlusterFS.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.