Distributed storage evaluation on a three-wide inter-data center deployment

2013 ◽  
Author(s):  
Yih-Farn Chen ◽  
Scott Daniels ◽  
Marios Hadjieleftheriou ◽  
Pingkai Liu ◽  
Chao Tian ◽  
...  
Keyword(s):  
Data Center ◽  
Distributed Storage

A Novel Hash Chain-Based Data Availability Monitoring Method for Off-site Disaster Recovery Architecture

2021 ◽  
pp. 2150294
Author(s):  
Neng Huang ◽  
Junxing Zhu ◽  
Chaonian Guo ◽  
Shuhan Cheng ◽  
Xiaoyong Li
Keyword(s):  
Information Systems ◽  
Real Time ◽  
Data Center ◽  
Disaster Recovery ◽  
Distributed Storage ◽  
Data Availability ◽  
Data Consistency ◽  
Real Time Monitoring ◽  
The Real ◽  
Hash Chain

With the rapid development of mobile Internet, there is a higher demand for the real-time, reliability and availability of information systems and to prevent the possible systemic risks of information systems, various business consistency standards and regulatory guidelines have been published, such as Recovery Time Object (RTO) and Recovery Point Object (RPO). Some of the current related researches focus on the standards, methods, management tools and technical frameworks of business consistency, while others study the data consistency algorithms in the cases of large data, cloud computing and distributed storage. However, few researchers have studied on how to monitor the data consistency and RPO of production-disaster recovery, and what architecture and technology should be applied in the monitoring. Moreover, in some information systems, due to the complex structures and distributions of data, it is difficult for traditional methods to quickly detect and accurately locate the first error data. Besides, due to the separation of production data center (PDC) and disaster recovery data center (DRDC), it is difficult to calculate the data difference and RPO between the two centers. This paper first discusses the architecture of remote distributed DRDCs. The architecture can make the disaster recovery (DR) system always online and the data always readable, and support the real-time monitoring of data availability, consistency as well as other related indicators, in this way to make DRDC out-of-the-box in disasters. Second, inspired by blockchain, this paper proposes a method to realize real-time monitoring of data consistency and RTO by building hash chains for PDC and DRDC. Third, this paper evaluates the hash chain operations from the algorithm time complexity, the data consistency, and the validity of RPO monitoring algorithms and since DR system is actually a kind of distributed system, the proposed approach can also be applied to the data consistency detection and data difference monitoring in other distributed systems.

scholarly journals DESIGN AND VERIFICATION OF REMOTE SENSING IMAGE DATA CENTER STORAGE ARCHITECTURE BASED ON HADOOP

2018 ◽  
Vol XLII-3 ◽  
pp. 1639-1642
Author(s):  
D. Tang ◽  
X. Zhou ◽  
Y. Jing ◽  
W. Cong ◽  
C. Li
Keyword(s):  
Remote Sensing ◽  
Data Storage ◽  
Data Center ◽  
High Speed ◽  
Large Scale ◽  
Distributed Storage ◽  
Image Data ◽  
Remotely Sensed Data ◽  
Processing Technologies ◽  
Data Parallel

The data center is a new concept of data processing and application proposed in recent years. It is a new method of processing technologies based on data, parallel computing, and compatibility with different hardware clusters. While optimizing the data storage management structure, it fully utilizes cluster resource computing nodes and improves the efficiency of data parallel application. This paper used mature Hadoop technology to build a large-scale distributed image management architecture for remote sensing imagery. Using MapReduce parallel processing technology, it called many computing nodes to process image storage blocks and pyramids in the background to improve the efficiency of image reading and application and sovled the need for concurrent multi-user high-speed access to remotely sensed data. It verified the rationality, reliability and superiority of the system design by testing the storage efficiency of different image data and multi-users and analyzing the distributed storage architecture to improve the application efficiency of remote sensing images through building an actual Hadoop service system.

scholarly journals A Secured Data Retrieval Architecture for WBAN using Elliptic Curve Digital Signature

2019 ◽  
Vol 8 (10) ◽  
pp. 4275-4279
Keyword(s):  
Big Data ◽  
Elliptic Curve ◽  
Digital Signature ◽  
Data Center ◽  
Distributed Storage ◽  
Wireless Body Area Network ◽  
Data Retrieval ◽  
Sensor Nodes ◽  
Area Network ◽  
Certification Authority

The big data is proposed a secure scheme of data collection that to deal the problems in WBAN (Wireless Body Area Network). To start with to register the sensor nodes using CA (Certification Authority) connect the Network of Big data center. After the preprocessing stage, the sensors are correlated with big data center through authentication on both sides by ECDSA (Elliptic Curve Digital Signature Algorithm). The sensor node designed using distributed storage and the collected data transfer with improved security protection.

Research on Distributed Heterogeneous Data Storage Algorithm in Cloud Computing Data Center

2014 ◽  
Vol 624 ◽  
pp. 553-556
Author(s):  
Jing Bo Yang ◽  
Shu Huang ◽  
Pan Jiang
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Center ◽  
Data Stream ◽  
Large Scale ◽  
Distributed Storage ◽  
Heterogeneous Data ◽  
Allocation Problem ◽  
Data Consistency ◽  
Storage Allocation

With the development of cloud computing, data center is also improved. cloud computing data center contains hundreds, even million of servers or PCs. It has many heterogeneous resources. Data center is a key to promise high scalability and resource usage of cloud computing. In addition, replica is introduced into data center, which is an important method to improve availability and performance. In this paper, the research on distributed storage algorithm based on the cloud computing. This algorithm uses the design of system storage level indicators within classification of massive data storage mechanism to solve the allocation problem of data consistency between the data center; and send communication packets between data centers through the cloud computing. The full storage can achieve complete local storage of each data stream, and solve the original data stream unusually large-scale data storage allocation problem.

A Distributed Storage Algorithm Based on Cauchy RS Code

2013 ◽  
Vol 336-338 ◽  
pp. 2188-2194
Author(s):  
Xing Gao ◽  
Min Li ◽  
Juan Juan Huang ◽  
Bing Chang Liu
Keyword(s):  
Fault Tolerance ◽  
Data Center ◽  
Distributed Storage ◽  
Erasure Codes ◽  
Data Encoding ◽  
Multiplication Operation ◽  
Rs Code ◽  
Rs Coding ◽  
Encoding Efficiency ◽  
Better Than

Data fault tolerance is a key technology in the field of distributed storage. In this paper, an algorithm to encode massive amounts of data and then distribute storage these data on each node in the data center is proposed, aiming at coping with the serious challenges in the protection of data fault tolerance. The method converts multiplication operation in Cauchy RS coding into a binary multiplication through the transition on bit operation, so that the entire operation on RS encoding is converted to an operation containing only simple XOR operator. The experiment proves that the method is better than the copy and the original RS coding in the data encoding efficiency. Furthermore, it saves the storage space and promotes the application of erasure codes strongly in distributed storage field.

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