A high performance private cloud storage system

2014 ◽  
Author(s):  
Wei Zhang
Keyword(s):  
Cloud Storage ◽  
High Performance ◽  
Storage System ◽  
Private Cloud

Ubackup: An Easy Way to Build a High-Efficient Private Cloud Storage System

2014 ◽  
Vol 556-562 ◽  
pp. 6241-6245 ◽  
Author(s):  
Kai Guo ◽  
Peng Yan Shen ◽  
Ming Zhong Xiao
Keyword(s):  
Cloud Storage ◽  
Storage System ◽  
Utilization Rate ◽  
Private Cloud ◽  
Erasure Code ◽  
Balance System ◽  
High Efficient ◽  
Code Algorithm ◽  
Disaster Tolerance ◽  
The Cost

In this paper, we present UBackup, which describes an easy way to build a private cloud storage system with high-efficient and high-disaster-tolerance. UBackup client enables file-level de-duplication by using a file fingerprint check. The utilization of compressed erasure code algorithm ensures data security and cuts down the cost. A space utilization rate variance minimizing algorithm is used on index server to balance system load. We present the system architecture of UBackup and its components, and we have implemented a proof-of-concept prototype of UBackup. By conducting performance evaluation in a public Internet, experimental results demonstrate the efficiency of the system.

Data Consistency Research of the Cloud Storage Environment Based on P2P Technology

2013 ◽  
Vol 380-384 ◽  
pp. 2589-2592
Author(s):  
Jun Wei Ge ◽  
Feng Yang ◽  
Yi Qiu Fang
Keyword(s):  
Cloud Storage ◽  
High Performance ◽  
Storage System ◽  
Model Systems ◽  
Data Consistency ◽  
Service Reliability ◽  
Cloud Storage Environment ◽  
P2p Technology ◽  
Server Architecture

Many of the characteristics of P2P technology such as decentralization, scalability, robustness, high performance and load balancing are in line with the cloud storage design requirements. In this article, it proposesd a cloud storage model based on P2P technology. This model uses multivariate data server architecture, which can effectively solve the bottleneck problem of centralized cloud storage system. Thereby increasing the cloud storage system performance and the quality of cloud storage services, enhance service reliability. In this article, through researching data consistency algorithm named Paxos and the model systems metadata consistency problem, we improve and optimize Basic Paxos making it applied in the model system.

Data Storage Technology and its Development Based on Cloud Computing

2013 ◽  
Vol 756-759 ◽  
pp. 1275-1279
Author(s):  
Lin Na Huang ◽  
Feng Hua Liu
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Cloud Storage ◽  
High Performance ◽  
File System ◽  
Storage System ◽  
Distributed File System ◽  
Cloud Data ◽  
Storage Technology ◽  
Cloud Data Storage

Cloud storage of high performance is the basic condition for cloud computing. This article introduces the concept and advantage of cloud storage, discusses the infrastructure of cloud storage system as well as the architecture of cloud data storage, researches the details about the design of Distributed File System within cloud data storage, at the same time, puts forward different developing strategies for the enterprises according to the different roles that the enterprises are acting as during the developing process of cloud computing.

Design of High Performance Cloud Storage Platform Based on Cheap PC Clusters Using MongoDB and Hadoop

2013 ◽  
Vol 380-384 ◽  
pp. 2050-2053
Author(s):  
Cheng Dai ◽  
Yan Ye ◽  
Tai Jun Liu ◽  
Jing Jing Zheng
Keyword(s):  
Data Analysis ◽  
Cloud Storage ◽  
High Performance ◽  
Unstructured Data ◽  
Map Reduce ◽  
Complex Data ◽  
Private Cloud ◽  
Computer Clusters ◽  
Nosql Database ◽  
Key Technologies

To lay the foundation for the high performance private cloud storage platform, this paper proposes a new cloud storage structure with horizontal scalability using MongoDB and Hadoop. MongoDB is a powerful NOSQL database which is used to construct the cloud storage platform. In certain scenarios, the map-reduce provided by MongoDB can not meet the need of the complex data analysis, especially for the mass complex unstructured data such as videos and documents. This paper introduce the key technologies in MongoDB and Hadoop, then aggregate the advantages of them to build a high performance private cloud storage infrastructure based on cheap personal computer clusters. This infrastructure combines the high horizontal scalability of MongoDB and the high-performance analysis capability from Hadoop.

scholarly journals A New Hybrid Automated Security Framework to Cloud Storage System

Cryptography ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 37
Author(s):  
Noha E. El-Attar ◽  
Doaa S. El-Morshedy ◽  
Wael A. Awad
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Data Privacy ◽  
High Performance ◽  
Storage System ◽  
Third Party ◽  
File Size ◽  
Cloud Data ◽  
Security Issues ◽  
User Data

The need for cloud storage grows day after day due to its reliable and scalable nature. The storage and maintenance of user data at a remote location are severe issues due to the difficulty of ensuring data privacy and confidentiality. Some security issues within current cloud systems are managed by a cloud third party (CTP), who may turn into an untrustworthy insider part. This paper presents an automated Encryption/Decryption System for Cloud Data Storage (AEDS) based on hybrid cryptography algorithms to improve data security and ensure confidentiality without interference from CTP. Three encryption approaches are implemented to achieve high performance and efficiency: Automated Sequential Cryptography (ASC), Automated Random Cryptography (ARC), and Improved Automated Random Cryptography (IARC) for data blocks. In the IARC approach, we have presented a novel encryption strategy by converting the static S-box in the AES algorithm to a dynamic S-box. Furthermore, the algorithms RSA and Twofish are used to encrypt the generated keys to enhance privacy issues. We have evaluated our approaches with other existing symmetrical key algorithms such as DES, 3DES, and RC2. Although the two proposed ARC and ASC approaches are more complicated, they take less time than DES, DES3, and RC2 in processing the data and obtaining better performance in data throughput and confidentiality. ARC outperformed all of the other algorithms in the comparison. The ARC’s encrypting process has saved time compared with other algorithms, where its encryption time has been recorded as 22.58 s for a 500 MB file size, while the DES, 3DES, and RC2 have completed the encryption process in 44.43, 135.65, and 66.91 s, respectively, for the same file size. Nevertheless, when the file sizes increased to 2.2 GB, the ASC proved its efficiency in completing the encryption process in less time.

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