ISCAS OpenIR
A distributed cache framework for metadata service of distributed file systems
Sun, Yao (1); Liu, Jie (2); Ye, Dan (2); Zhong, Hua (2)
2013
Conference Name2013 19th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2013
Pages51-58
Conference DateDecember 15, 2013 - December 18, 2013
Conference PlaceSeoul, Korea, Republic of
Indexed TypeEI
Publish PlaceIEEE Computer Society
ISSN15219097
ISBN9781479920815
Department(1) University of Chinese Academy of Sciences, Beijing, China; (2) Institute of Software, Chinese Academy of Sciences, Beijing, China
English AbstractMost recent distributed file systems have adopted architecture with an independent metadata server cluster. However, potential multiple hotspots and flash crowds access patterns often cause a metadata service that violates performance Service Level Objectives. To maximize the throughput of the metadata service, an adaptive request load balancing framework is critical. We present a distributed cache framework above the distributed metadata management schemes to manage hotspots rather than managing all metadata to achieve request load balancing. This benefits the metadata hierarchical locality and the system scalability. Compared with data, metadata has its own distinct characteristics, such as small size and large quantity. The cost of useless metadata prefetching is much less than data prefetching. In light of this, we devise a time period-based prefetching strategy and a perfecting-based adaptive replacement cache algorithm to improve the performance of the distributed caching layer to adapt constantly changing workloads. Finally, we evaluate our approach with a hadoop distributed file system cluster. © 2013 IEEE.; Most recent distributed file systems have adopted architecture with an independent metadata server cluster. However, potential multiple hotspots and flash crowds access patterns often cause a metadata service that violates performance Service Level Objectives. To maximize the throughput of the metadata service, an adaptive request load balancing framework is critical. We present a distributed cache framework above the distributed metadata management schemes to manage hotspots rather than managing all metadata to achieve request load balancing. This benefits the metadata hierarchical locality and the system scalability. Compared with data, metadata has its own distinct characteristics, such as small size and large quantity. The cost of useless metadata prefetching is much less than data prefetching. In light of this, we devise a time period-based prefetching strategy and a perfecting-based adaptive replacement cache algorithm to improve the performance of the distributed caching layer to adapt constantly changing workloads. Finally, we evaluate our approach with a hadoop distributed file system cluster. © 2013 IEEE.
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/16686
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Sun, Yao ,Liu, Jie ,Ye, Dan ,et al. A distributed cache framework for metadata service of distributed file systems[C]. IEEE Computer Society,2013:51-58.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Sun, Yao (1)]'s Articles
[Liu, Jie (2)]'s Articles
[Ye, Dan (2)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Sun, Yao (1)]'s Articles
[Liu, Jie (2)]'s Articles
[Ye, Dan (2)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Sun, Yao (1)]'s Articles
[Liu, Jie (2)]'s Articles
[Ye, Dan (2)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.