scholarly journals Design and Implementation of Storage System Based on Big Data

2018 ◽  
Vol 228 ◽  
pp. 01012
Author(s):  
Biao Wan
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Cloud Storage ◽  
Storage System ◽  
Massive Data ◽  
Storage Model ◽  
Design And Implementation ◽  
The Times ◽  
Storage Technologies ◽  
And Storage

In the era of big data, the storage of massive data has become an important issue that enterprises need to solve. However, the existing storage model hinders the pace of the times, and new storage technologies and storage models that adapt to the development of the times must be studied. This paper first summarizes and summarizes the problems faced by Big Data, then proposes and analyzes popular cloud storage and cloud computing for storage problems, discusses its structure and models, introduces such technologies, and will lead the development of the times.

scholarly journals Encryption-Based Secure and Efficient Access Control to Out Sourced Data in Cloud Computing

2018 ◽  
Vol 7 (2.32) ◽  
pp. 315
Author(s):  
V Naresh ◽  
M Anudeep ◽  
M Saipraneeth ◽  
A Saikumar Reddy ◽  
V Navya
Keyword(s):  
Cloud Computing ◽  
Information Exchange ◽  
Cloud Storage ◽  
Storage System ◽  
Access Policy ◽  
File Access ◽  
Secure Information ◽  
Efficient Access ◽  
Security Certifications ◽  
And Storage

The cloud stockpiling framework, comprising of capacity servers, gives long haul stockpiling administrations on the Internet. Maintaining the data in the cloud computing of third parties generates: serious concern about the confidentiality of data and the reduction of data management costs. Nonetheless, we should give security certifications to outside information. We plan and actualize a protected cloud stockpiling framework that gives secure, secure and available record security for document administration and secure information exchange. It includes foreign files with a file access policy, possibly deleting files, to avoid being denied to anyone with a file access policy. To achieve these security objectives, a set of password keys is implemented that maintain a host (s) or head (s) separately. We offer a twofold edge intermediary coding plan and incorporate it with a decentralized disposal code, which is detailed with a safely Cloud storage framework. The Cloud storage system not only provides a secure and stable search and storage of data, but also allows the user to transfer their data to the user of the backup to another user without the data being returned.  

High-Throughput Encryption for Cloud Computing Storage System

2015 ◽  
pp. 2274-2287
Author(s):  
Yaser Jararweh ◽  
Ola Al-Sharqawi ◽  
Nawaf Abdulla ◽  
Lo'ai Tawalbeh ◽  
Mohammad Alhammouri
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Cloud Storage ◽  
High Performance ◽  
Storage System ◽  
Massive Data ◽  
Efficient Manner ◽  
Storage Security ◽  
Cloud Data ◽  
Cloud Data Storage

In recent years Cloud computing has become the infrastructure which small and medium-sized businesses are increasingly adopting for their IT and computational needs. It provides a platform for high performance and throughput oriented computing, and massive data storage. Subsequently, novel tools and technologies are needed to handle this new infrastructure. One of the biggest challenges in this evolving field is Cloud storage security, and accordingly we propose new optimized techniques based on encryption process to achieve better storage system security. This paper proposes a symmetric block algorithm (CHiS-256) to encrypt Cloud data in efficient manner. Also, this paper presents a novel partially encrypted metadata-based data storage. The (CHiS-256) cipher is implemented as part of the Cloud data storage service to offer a secure, high-performance and throughput Cloud storage system. The results of our proposed algorithm are promising and show the methods to be advantageous in Cloud massive data storage and access applications.

High-Throughput Encryption for Cloud Computing Storage System

2014 ◽  
Vol 4 (2) ◽  
pp. 1-14 ◽  
Author(s):  
Yaser Jararweh ◽  
Ola Al-Sharqawi ◽  
Nawaf Abdulla ◽  
Lo'ai Tawalbeh ◽  
Mohammad Alhammouri
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Cloud Storage ◽  
High Performance ◽  
Storage System ◽  
Massive Data ◽  
Efficient Manner ◽  
Cloud Data ◽  
Block Algorithm ◽  
Cloud Data Storage

In recent years Cloud computing has become the infrastructure which small and medium-sized businesses are increasingly adopting for their IT and computational needs. It provides a platform for high performance and throughput oriented computing, and massive data storage. Subsequently, novel tools and technologies are needed to handle this new infrastructure. One of the biggest challenges in this evolving field is Cloud storage security, and accordingly we propose new optimized techniques based on encryption process to achieve better storage system security. This paper proposes a symmetric block algorithm (CHiS-256) to encrypt Cloud data in efficient manner. Also, this paper presents a novel partially encrypted metadata-based data storage. The (CHiS-256) cipher is implemented as part of the Cloud data storage service to offer a secure, high-performance and throughput Cloud storage system. The results of our proposed algorithm are promising and show the methods to be advantageous in Cloud massive data storage and access applications.

The Research on Hadoop and Cloud Computing-Based Mass Data Storage Model of Computation

2011 ◽  
Vol 130-134 ◽  
pp. 2899-2902 ◽  
Author(s):  
Fang Peng ◽  
Qing Yun Huang ◽  
Zhao Peng Qian
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Business Model ◽  
Low Cost ◽  
Massive Data ◽  
Distributed Software ◽  
Computer Cluster ◽  
Storage Model ◽  
New Business ◽  
And Storage

Cloud computing as a new business model that allows the user according to their needs using the resource pool which formed by data on a large number of computers. Hadoop, as the distributed software platform is the most widely use of cloud computing. It can run applications on the computer cluster which formed by a large number of low-cost hardware devices, and turn the calculation into data completely then deal with massive data. This article describes the basic framework of Hadoop and the advantages of dealing with massive data, the concept of cloud computing, and research of computing and storage model which base on Hadoop and cloud computing.

Building OLAP Cubes From Columnar NoSQL Data Warehouses

2019 ◽  
pp. 129-157
Author(s):  
Khaled Dehdouh
Keyword(s):  
Big Data ◽  
Database System ◽  
Massive Data ◽  
Data Warehouses ◽  
Online Analysis ◽  
Storage Model ◽  
Data Cubes ◽  
Nosql Database ◽  
Oriented Approach

In the big data warehouses context, a column-oriented NoSQL database system is considered as the storage model which is highly adapted to data warehouses and online analysis. Indeed, the use of NoSQL models allows data scalability easily and the columnar store is suitable for storing and managing massive data, especially for decisional queries. However, the column-oriented NoSQL DBMS do not offer online analysis operators (OLAP). To build OLAP cubes corresponding to the analysis contexts, the most common way is to integrate other software such as HIVE or Kylin which has a CUBE operator to build data cubes. By using that, the cube is built according to the row-oriented approach and does not allow to fully obtain the benefits of a column-oriented approach. In this chapter, the main contribution is to define a cube operator called MC-CUBE (MapReduce Columnar CUBE), which allows building columnar NoSQL cubes according to the columnar approach by taking into account the non-relational and distributed aspects when data warehouses are stored.

scholarly journals Security control heterogeneous big data cloud storage system based on adaptive cache

2020 ◽  
Vol 1486 ◽  
pp. 052014
Author(s):  
Jianbao Zhu ◽  
Jing Fu ◽  
Yuwei Sun ◽  
Ye Shi ◽  
Yu Chen ◽  
...  
Keyword(s):  
Big Data ◽  
Cloud Storage ◽  
Storage System ◽  
Security Control ◽  
Adaptive Cache

scholarly journals SLA-aware resource scheduling algorithm for cloud storage

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Yong Wang ◽  
Xiaoling Tao ◽  
Feng Zhao ◽  
Bo Tian ◽  
Akshita Maradapu Vera Venkata Sai
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Scheduling Algorithm ◽  
The Public ◽  
Computing Paradigm ◽  
Self Service ◽  
End Node ◽  
Violation Rate ◽  
And Storage ◽  
Compare And Contrast

AbstractCloud computing is a novel computing paradigm, which connects plenty of computing resources and storage resources via Internet. Cloud computing provides a number of high-quality services, such as cloud storage, outsourcing computing, and on-demand self-service, which have been widely accepted by the public. In cloud computing, by submitting their tasks to cloud, plenty of applications share huge computation and storage resources. However, how to schedule resource efficiently is a big challenge in cloud computing.In this paper, we propose a SLA-aware resource algorithm to enable cloud storage more efficiently. In our scheme, we take advantage of the back-end node space utilization and I/O throughput comprehensively simultaneously. We compare and contrast the existing scheduling storage policies by implementing those algorithms. The extensive tests show that our algorithm achieves a considerable improvement in terms of violation rate and the number of used hosts.

scholarly journals Research and Application of Massive Data Processing in Oil Services

2012 ◽  
Vol 6-7 ◽  
pp. 1036-1040
Author(s):  
Bao An Li
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Rapid Growth ◽  
Massive Data ◽  
Oil Drilling ◽  
Data Problem ◽  
Traditional Industry ◽  
Massive Data Processing

Big data problem has caused widespread concern from industry to academia in recent years. As the amount of data produced by various industries and sectors of rapid growth, increasing demands on data processing and analysis capabilities, how to face the challenges of data, discover new opportunities, the issue has received wide attention. As a traditional industry, the oil drilling or refinery enterprise is facing the operational status of the system to produce large amounts of data. This text introduced an approach to massive data processing for oil enterprise based on cloud computing and Internet of Things.

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