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.

A Multi-Server Erasure Code Algorithm Based on the Degree of Restriction

2013 ◽  
Vol 717 ◽  
pp. 789-793
Author(s):  
Jun Wei Ge ◽  
Ai Hua Miao ◽  
Yi Qiu Fang
Keyword(s):  
System Performance ◽  
Cloud Storage ◽  
Storage System ◽  
Erasure Codes ◽  
Storage Space ◽  
High Recovery ◽  
Erasure Code ◽  
Code Algorithm ◽  
Cloud Storage Environment ◽  
Multi Server

Erasure codes received extensive attention in the cloud storage system because of its effective on saving storage space,However, due to the high recovery-overhead of erasure code, its application has been limited in these storage systems.For these problems,in this paper,we presents A multi-server Erasure code algorithm based on the degree of restriction to reduce the recovery-overhead from the restriction of date and parity's degree,and enhance the system performance to a certain extent ,ensure the reliability of the data of the cloud storage environment.

Research of Cloud Storage and Improved Distributed Strategy of Data Storage

2014 ◽  
Vol 496-500 ◽  
pp. 1812-1816 ◽  
Author(s):  
Hong Xia Mao
Keyword(s):  
Load Balancing ◽  
Data Storage ◽  
Cloud Storage ◽  
Storage System ◽  
Utilization Rate ◽  
Consistent Hashing ◽  
Storage Node ◽  
Load Rate ◽  
Hashing Algorithm ◽  
System Prototype

In this paper, an extensible system prototype of cloud storage is designed. Considering the load balance of cloud storage system, an improved data storage strategy based on consistent hashing algorithm is proposed in this paper. The strategy adopts virtual nodes to storage data and real–time monitoring of load rate of each storage node to adjust load balancing of the whole storage system. In the improved strategy, the priority is introduced into the storage system to rapidly improve the utilization rate of the new storage nodes. The strategy can effectively optimize the performance of the whole storage system, and improve the overall effect of the load balancing.

Single node repair algorithm for a multimedia cloud storage system based on network coding

2021 ◽  
Vol 27 (3) ◽  
pp. 205-214
Author(s):  
Xin Niu ◽  
Jingjing Jiang
Keyword(s):  
Network Coding ◽  
Cloud Storage ◽  
Storage System ◽  
University Teaching ◽  
Easy Access ◽  
Single Node ◽  
Storage Cost ◽  
Multimedia Cloud ◽  
Code Algorithm ◽  
Node Repair

Multimedia is inconvenient to use, difficult to maintain, and redundant in data storage. In order to solve the above problems and apply cloud storage to the integration of university teaching resources, this paper designs a virtualized cloud storage platform for university multimedia classrooms. The platform has many advantages, such as reducing the initial investment in multimedia classrooms, simplifying management tasks, making maximum use of actual resources and easy access to resources. Experiments and analysis show the feasibility and effectiveness of the platform. Aiming at the problems of the single-node repair algorithm of the existing multimedia cloud storage system, the limited domain is large, the codec complexity is high, the disk I/O (Input/Output) cost is high, the storage overhead and the repair bandwidth are unbalanced, and a network coding-based approach is proposed. Multimedia cloud storage. System single node repair algorithm. The algorithm stores the grouped multimedia file data in groups in the system, and performs XOR (exclusive OR) on the data in the group on the GF(2) finite field. When some nodes fail, the new node only needs to be connected. Two to three non-faulty nodes in the same group can accurately repair the data in the failed node. Theoretical analysis and simulation results show that the algorithm can reduce the complexity and repair of the codec, and reduce the disk I/O overhead. In this case, the storage cost of the algorithm is consistent with the storage cost based on the minimum storage regeneration code algorithm, and the repair bandwidth cost is close to the minimum bandwidth regeneration code algorithm.

scholarly journals BMCloud: Minimizing Repair Bandwidth and Maintenance Cost in Cloud Storage

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Chao Yin ◽  
Changsheng Xie ◽  
Jiguang Wan ◽  
Chih-Cheng Hung ◽  
Jinjiang Liu ◽  
...  
Keyword(s):  
Fault Tolerance ◽  
Cloud Storage ◽  
Storage System ◽  
The Other ◽  
Maintenance Cost ◽  
Erasure Code ◽  
Networked Storage ◽  
Efficient Recovery ◽  
System Prototype ◽  
Exact Repair

To protect data in cloud storage, fault tolerance and efficient recovery become very important. Recent studies have developed numerous solutions based on erasure code techniques to solve this problem using functional repairs. However, there are two limitations to address. The first one is consistency since the Encoding Matrix (EM) is different among clouds. The other one is repairing bandwidth, which is a concern for most of us. We addressed these two problems from both theoretical and practical perspectives. We developed BMCloud, a new low repair bandwidth, low maintenance cost cloud storage system, which aims to reduce repair bandwidth and maintenance cost. The system employs both functional repair and exact repair while it inherits advantages from the both. We propose the JUDGE_STYLE algorithm, which can judge whether the system should adopt exact repair or functional repair. We implemented a networked storage system prototype and demonstrated our findings. Compared with existing solutions, BMCloud can be used in engineering to save repair bandwidth and degrade maintenance significantly.

scholarly journals Authentication Based Cloud Storage and Secure Data Forwarding

2013 ◽  
Vol 4 (1) ◽  
pp. 106-110
Author(s):  
Rajasekaran S ◽  
Kalifulla. Y ◽  
Murugesan. S ◽  
Ezhilvendan. M ◽  
Gunasekaran. J
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Distributed Storage ◽  
Storage System ◽  
Encryption Scheme ◽  
Data Confidentiality ◽  
Distributed Storage System ◽  
Erasure Code ◽  
Long Term Storage ◽  
Storage Servers

cloud storage system, consisting of a collection of storage servers, provides long-term storage services over the Internet.  Storing data in a third party’s cloud system causes serious concern over data confidentiality. General encryption schemes protect data confidentiality, but also limit the functionality of the storage system because a few operations are supported over encrypted data. Constructing a secure storage system that supports multiple functions is challenging when the storage system is distributed and has no central authority. We propose a threshold proxy re-encryption scheme and integrate it with a decentralized erasure code such that a secure distributed storage system is formulated. The distributed storage system not only supports secure and robust data storage and retrieval, but also lets a user forward his data in the storage servers to another user without retrieving the data back. The main technical contribution is that the proxy re-encryption scheme supports encoding operations over encrypted messages as well as forwarding operations over encoded and encrypted messages. Our method fully integrates encrypting, encoding, and forwarding. We analyze and suggest suitable parameters for the number of copies of a message dispatched to storage servers and the number of storage servers queried by a key server. These parameters allow more flexible adjustment between the number of storage servers and robustness.

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