A Study and Design on the Data Storage Management Methods in Mobile Environment

2016 ◽  
Author(s):  
Guest Editor Huier Liu
Keyword(s):  
Data Storage ◽  
Storage Management ◽  
Mobile Environment

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

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

Mobile Cloud Computing

2015 ◽  
pp. 1-23
Author(s):  
Jyoti Grover ◽  
Gaurav Kheterpal
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Storage ◽  
Mobile Applications ◽  
Large Scale ◽  
Mobile Cloud Computing ◽  
Research Area ◽  
Computation Offloading ◽  
Mobile Cloud ◽  
Mobile Environment

Mobile Cloud Computing (MCC) has become an important research area due to rapid growth of mobile applications and emergence of cloud computing. MCC refers to integration of cloud computing into a mobile environment. Cloud providers (e.g. Google, Amazon, and Salesforce) support mobile users by providing the required infrastructure (e.g. servers, networks, and storage), platforms, and software. Mobile devices are rapidly becoming a fundamental part of human lives and these enable users to access various mobile applications through remote servers using wireless networks. Traditional mobile device-based computing, data storage, and large-scale information processing is transferred to “cloud,” and therefore, requirement of mobile devices with high computing capability and resources are reduced. This chapter provides a survey of MCC including its definition, architecture, and applications. The authors discuss the issues in MCC, existing solutions, and approaches. They also touch upon the computation offloading mechanism for MCC.

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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