The new storage [business data storage management]

2005 ◽  
Vol 2 (6) ◽  
pp. 20-22
Author(s):  
P. Hunter
Keyword(s):  
Data Storage ◽  
Storage Management ◽  
Business Data

Archive drive [business data storage]

2005 ◽  
Vol 2 (2) ◽  
pp. 34-38
Author(s):  
S. Tongish
Keyword(s):  
Data Storage ◽  
Business Data

Data Storage Management in Cloud Environments

2018 ◽  
Vol 50 (6) ◽  
pp. 1-51 ◽  
Author(s):  
Yaser Mansouri ◽  
Adel Nadjaran Toosi ◽  
Rajkumar Buyya
Keyword(s):  
Data Storage ◽  
Storage Management ◽  
Cloud Environments

scholarly journals Heterogeneous Data Storage Management with Deduplication in Cloud Computing

2019 ◽  
Vol 5 (3) ◽  
pp. 393-407 ◽  
Author(s):  
Zheng Yan ◽  
Lifang Zhang ◽  
Wenxiu Ding ◽  
Qinghua Zheng
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Heterogeneous Data ◽  
Storage Management

Overview of Big Data-Intensive Storage and its Technologies for Cloud and Fog Computing

2021 ◽  
pp. 112-153
Author(s):  
Richard S. Segall ◽  
Jeffrey S Cook ◽  
Gao Niu
Keyword(s):  
Big Data ◽  
Data Storage ◽  
High Performance ◽  
Storage Systems ◽  
Fog Computing ◽  
Storage Management ◽  
Data Intensive Computing ◽  
Computing Systems ◽  
Application Performance ◽  
Data Intensive

Computing systems are becoming increasingly data-intensive because of the explosion of data and the needs for processing the data, and subsequently storage management is critical to application performance in such data-intensive computing systems. However, if existing resource management frameworks in these systems lack the support for storage management, this would cause unpredictable performance degradation when applications are under input/output (I/O) contention. Storage management of data-intensive systems is a challenge. Big Data plays a most major role in storage systems for data-intensive computing. This article deals with these difficulties along with discussion of High Performance Computing (HPC) systems, background for storage systems for data-intensive applications, storage patterns and storage mechanisms for Big Data, the Top 10 Cloud Storage Systems for data-intensive computing in today's world, and the interface between Big Data Intensive Storage and Cloud/Fog Computing. Big Data storage and its server statistics and usage distributions for the Top 500 Supercomputers in the world are also presented graphically and discussed as data-intensive storage components that can be interfaced with Fog-to-cloud interactions and enabling protocols.

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