Study on Cloud Storage System Based on Distributed Storage Systems

2010 ◽  
Author(s):  
Qinlu He ◽  
Zhanhuai Li ◽  
Xiao Zhang
Keyword(s):  
Cloud Storage ◽  
Storage Systems ◽  
Distributed Storage ◽  
Storage System ◽  
Distributed Storage Systems

Commercial and Distributed Storage Systems

2013 ◽  
pp. 1-8 ◽  
Author(s):  
Spyridon V. Gogouvitis ◽  
Athanasios Voulodimos ◽  
Dimosthenis Kyriazis
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Storage Systems ◽  
Distributed Storage ◽  
End Users ◽  
Digital Environment ◽  
Storage Solutions ◽  
Distributed Storage Systems ◽  
Promising Solution ◽  
New Generation

Distributed storage systems are becoming the method of data storage for the new generation of applications, as it appears a promising solution to handle the immense volume of data produced in today’s rich and ubiquitous digital environment. In this chapter, the authors first present the requirements end users pose on Cloud Storage solutions. Then they compare some of the most prominent commercial distributed storage systems against these requirements. Lastly, the authors present the innovations the VISION Cloud project brings in the field of Storage Clouds.

scholarly journals PRELIMINARY STUDY ON APPLICATION OF MAX PLUS ALGEBRA IN DISTRIBUTED STORAGE SYSTEM THROUGH NETWORK CODING

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Agus Maman Abadi ◽  
Musthofa Musthofa ◽  
Emut Emut
Keyword(s):  
Network Coding ◽  
Data Storage ◽  
Algebraic Structure ◽  
Storage Systems ◽  
Distributed Storage ◽  
Storage System ◽  
Distributed Data Storage ◽  
Erasure Code ◽  
Distributed Storage Systems ◽  
Set Up

The increasing need in techniques of storing big data presents a new challenge. One way to address this challenge is the use of distributed storage systems. One strategy that implemented in distributed data storage systems is the use of Erasure Code which applied to network coding. The code used in this technique is based on the algebraic structure which is called as vector space. Some studies have also been carried out to create code that is based on other algebraic structures such as module.  In this study, we are going to try to set up a code based on the algebraic structure which is a generalization of the module that is semimodule by utilizing the max operations and sum operations at max plus algebra. The results of this study indicate that the max operation and the addition operation on max plus algebra cannot be used to establish a semimodule code, but by modifying the operation "+" as "min", we get a code based on semimodule. Keywords:   code, distributed storage systems, network coding, semimodule, max plus algebra

scholarly journals A survey on trade-off between storage and repair traffic in distributed storage systems

2018 ◽  
Vol 7 (2.8) ◽  
pp. 379
Author(s):  
D Sowmia ◽  
B Muruganantham
Keyword(s):  
Cloud Storage ◽  
Storage Systems ◽  
Distributed Storage ◽  
Large Data ◽  
Future Research ◽  
Access To Information ◽  
Storage Model ◽  
Distributed Storage Systems ◽  
Data Objects ◽  
Online Storage

Distributed storage systems give dependable access to information through excess spread over independently unreliable hubs. Application scenarios incorporate server farms, distributed capacity frameworks, and capacity in remote systems. This paper gives a study on the cloud storage model of networked online storage where data is stored in virtualized pools of storage which are generally hosted by third parties. Hosting companies operate large data centersand people who require their data to be encouraged buy or lease accumulating limit from them. The server cultivate overseers, outside of anyone's ability to see, virtualize the advantages according to the necessities of the customer and reveal them as limit pools, which the customers would themselves have the capacity to use to store records or data objects. . The data is stored across various locations, when the user wants to retrieve them, it could be done by any of the encryption methods. At last, in view of existing procedures, promising future research bearings are recommended.

Analysis of a Stochastic Model of Replication in Large Distributed Storage Systems

2017 ◽  
Vol 45 (1) ◽  
pp. 51-51
Author(s):  
Wen Sun ◽  
Véronique Simon ◽  
Sébastien Monnet ◽  
Philippe Robert ◽  
Pierre Sens
Keyword(s):  
Stochastic Model ◽  
Storage Systems ◽  
Distributed Storage ◽  
Distributed Storage Systems

Tree-Structured Parallel Regeneration Based on Regenerating Codes for Multiple Data Losses in Distributed Storage Systems

2014 ◽  
Vol 918 ◽  
pp. 295-300
Author(s):  
Peng Fei You ◽  
Yu Xing Peng ◽  
Zhen Huang ◽  
Chang Jian Wang
Keyword(s):  
Storage Systems ◽  
Distributed Storage ◽  
Data Loss ◽  
Data Reliability ◽  
Data Redundancy ◽  
Regeneration Time ◽  
Multiple Data ◽  
Distributed Storage Systems ◽  
Regenerating Codes ◽  
Reliability And Availability

In distributed storage systems, erasure codes represent an attractive data redundancy solution which can provide the same reliability as replication requiring much less storage space. Multiple data losses happens usually and the lost data should be regenerated to maintain data redundancy in distributed storage systems. Regeneration for multiple data losses is expected to be finished as soon as possible, because the regeneration time can influence the data reliability and availability of distributed storage systems. However, multiple data losses is usually regenerated by regenerating single data loss one by one, which brings high entire regeneration time and severely reduces the data reliability and availability of distributed storage systems. In this paper, we propose a tree-structured parallel regeneration scheme based on regenerating codes (TPRORC) for multiple data losses in distributed storage systems. In our scheme, multiple regeneration trees based on regenerating code are constructed. Firstly, these trees are created independently, each of which dose not share any edges from the others and is responsible for one data loss; secondly, every regeneration tree based on regenerating codes owns the least network traffic and bandwidth optimized-paths for regenerating its data loss. Thus it can perform parallel regeneration for multiple data losses by using multiple optimized topology trees, in which network bandwidth is utilized efficiently and entire regeneration is overlapped. Our simulation results show that the tree-structured parallel regeneration scheme reduces the regeneration time significantly, compared to other regular regeneration schemes.

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