Implementation and Analysis of the File System Based on Metadata Dynamic Hashing

2012 ◽  
Vol 490-495 ◽  
pp. 1034-1038
Author(s):  
Si Ma ◽  
Tao Cai ◽  
Yong Zhao Zhan

Metadata management algorithm plays an important role in file system performance and file system is the most common way of data accessing in mass storage systems, so metadata management algorithm is very important for the performance of mass storage system. In this paper we analyze current metadata management algorithms and bring in the metadata dynamic hashing algorithm to solve the problem of poor adaptability of them. We realize the prototype on Lustre. After testing system performance with common tools by adjusting the several parameters’ value of metadata dynamic hashing algorithm, we find that performance of the prototype I/O is superior to Lustre. Furthermore, we analyze impacts of the parameters of dynamic hashing function on I/O performance of prototype

2017 ◽  
Vol 898 ◽  
pp. 062003
Author(s):  
Qiulan Huang ◽  
Ran Du ◽  
YaoDong Cheng ◽  
Jingyan Shi ◽  
Gang Chen ◽  
...  

2012 ◽  
Vol 532-533 ◽  
pp. 818-822
Author(s):  
De Jiao Niu ◽  
Yong Zhao Zhan ◽  
Tao Cai

Metadata query plays an important role in mass storage system. Efficient indexing algorithm can reduce the time and space which greatly determine the efficiency of mass storage system. Typically, temporal and spatial consuming is immense and volatile in the existing metadata management algorithms. In this paper, a novel metadata indexing algorithm is presented. Metadata query algorithm is based on two-level indexing strategy. The metadata is classified into two categories, that are active metadata and non-active metadata. The Bloom Filter is used to generate binary string for active metadata, and the B-tree is used to establish index of each active partition. While, the suitable hash function is selected for each non-active metadata partition. The results show that the multi-level metadata indexing algorithm can reduce the temporal and spatial costs of metadata query.


2014 ◽  
Vol 556-562 ◽  
pp. 4009-4013
Author(s):  
Yi Jiang ◽  
Qiang Xiao ◽  
Rong Huang ◽  
An Ping Xiong

With the development of information technology, distributed file system is widely used in massive information storage. Usually, distributed file system uses metadata server to achieve quick access to files according to directory, thus the organization and management of metadata are the keys to the file system performance. In general, directory subtree partition method and hash algorithm are used by existing mass storage system to manage metadata. However, to solve the problems, like low access efficiency of metadata, ineffective balance of load and poor extensibility, in existing metadata management strategy of distributed file system, dynamic load balance strategy of metadata based on hash tags is put forward, in which the tags act as partition granularity and hot tags of metadata will be hashed again to achieve the goal of load balance. The experimental results in this paper turn out that modified metadata management strategy based on hash tags has greater system throughput and less average response time than the one based on tags.,


2018 ◽  
Vol 228 ◽  
pp. 01011
Author(s):  
Haifeng Zhong ◽  
Jianying Xiong

The wan Internet storage system based on Distributed Hash Table uses fully distributed data and metadata management, and constructs an extensible and efficient mass storage system for the application based on Internet. However, such systems work in highly dynamic environments, and the frequent entry and exit of nodes will lead to huge communication costs. Therefore, this paper proposes a new hierarchical metadata routing management mechanism based on DHT, which makes full use of the node stabilization point to reduce the maintenance overhead of the overlay. Analysis shows that the algorithm can effectively improve efficiency and enhance stability.


2015 ◽  
Vol 608 ◽  
pp. 012013 ◽  
Author(s):  
Pier Paolo Ricci ◽  
Alessandro Cavalli ◽  
Luca Dell'Agnello ◽  
Matteo Favaro ◽  
Daniele Gregori ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document