scholarly journals Multi-level Metadata Management Scheme for Cloud Storage System

2014 ◽  
Vol 9 (1) ◽  
pp. 231-240
Author(s):  
Jin San Kong ◽  
Min Ja Kim ◽  
Wan Yeon Lee ◽  
Chuck Yoo ◽  
Young Woong Ko
Keyword(s):  
Cloud Storage ◽  
Storage System ◽  
Metadata Management ◽  
Management Scheme ◽  
Multi Level

CloudS: A Multi-cloud Storage System with Multi-level Security

2015 ◽  
pp. 703-716 ◽  
Author(s):  
Lu Shen ◽  
Shifang Feng ◽  
Jinjin Sun ◽  
Zhongwei Li ◽  
Gang Wang ◽  
...  
Keyword(s):  
Cloud Storage ◽  
Storage System ◽  
Multi Level ◽  
Multi Cloud

scholarly journals Energy Efficient Metadata Management for Cloud Storage System

2015 ◽  
Vol 11 (9) ◽  
pp. 626575
Author(s):  
Young Woong Ko ◽  
Sun-Jeong Kim ◽  
Jin Kim ◽  
Eui-Jik Kim ◽  
Jung Min So
Keyword(s):  
Energy Efficient ◽  
Cloud Storage ◽  
Storage System ◽  
Metadata Management

scholarly journals CloudS: A Multi-Cloud Storage System with Multi-Level Security

2016 ◽  
Vol E99.D (8) ◽  
pp. 2036-2043 ◽  
Author(s):  
Lu SHEN ◽  
Shifang FENG ◽  
Jinjin SUN ◽  
Zhongwei LI ◽  
Ming SU ◽  
...  
Keyword(s):  
Cloud Storage ◽  
Storage System ◽  
Multi Level ◽  
Multi Cloud

The Multi-Level Metadata Indexing in Mass Storage System

2012 ◽  
Vol 532-533 ◽  
pp. 818-822
Author(s):  
De Jiao Niu ◽  
Yong Zhao Zhan ◽  
Tao Cai
Keyword(s):  
Hash Function ◽  
Storage System ◽  
Bloom Filter ◽  
Metadata Management ◽  
Mass Storage ◽  
Mass Storage System ◽  
Multi Level ◽  
Temporal And Spatial ◽  
Query Algorithm ◽  
Management Algorithms

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.

A Metadata Management Mechanism Based on HDFS

2014 ◽  
Vol 577 ◽  
pp. 1026-1029 ◽  
Author(s):  
Xiao Feng Chen ◽  
Yuan Sheng Lou ◽  
Dong Mei Hu
Keyword(s):  
Cloud Storage ◽  
Storage System ◽  
Original System ◽  
Basic Unit ◽  
Metadata Management ◽  
System Operation ◽  
Management Mechanism ◽  
Consistent Hashing ◽  
Multiple Servers ◽  
Local Cache

A metadata management mechanism on the basis of HDFS was proposed in this paper, which is applied for cloud storage. The basic unit of consistent hashing is DHU in the scheme. Metadata is distributed in multiple servers in this solution, and the position of metadata is recorded in a mapping table. In addition, prefetching strategy and local cache technology are used to improve the performance of the system. Operation logs and Multi-Paxos algorithm are being used to ensure system’s reliability and consistency. Improved system with a lower latency in reading and writing than the original system was seen in the experiments. Good performance for cloud storage system can be shown by this system.

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