scholarly journals The BNLBox Cloud Storage Service

2020 ◽  
Vol 245 ◽  
pp. 04011
Author(s):  
Ofer Rind ◽  
Hironori Ito ◽  
Guangwei Che ◽  
Tim Chou ◽  
Robert Hancock ◽  
...  
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Cloud Storage ◽  
Storage System ◽  
Data Access ◽  
Scientific Data ◽  
Data Management System ◽  
Easy Access ◽  
Cloud Storage Service ◽  
Storage Service

Large scientific data centers have recently begun providing a number of different types of data storage in order to satisfy the various needs of their users. Users with interactive accounts, for example, might want a POSIX interface for easy access to the data from their interactive machines. Grid computing sites, on the other hand, likely need to provide an X509-based storage protocol, like SRM and GridFTP, since the data management system is built upon them. Meanwhile, an experiment producing large amounts of data typically demands a service that provides archival storage for the safe keeping of their unique data. To access these various types of data, users must use specific sets of commands tailored to their respective storage, making access to their data complex and difficult. BNLBox is an attempt to provide a unified and easy to use storage service for all BNL users, to store their important documents, code and data. It is a cloud storage system with an intuitive web interface for novice users. It provides an automated synchronization feature that enables users to upload data to their cloud storage without manual intervention, freeing them to focus on analysis rather than data management software. It provides a POSIX interface for local interactive users, which simplifies data access from batch jobs as well. At the same time, it also provides users with a straightforward mechanism for archiving large data sets for later processing. The storage space can be used for both code and data within the compute job environment. This paper will describe various aspects of the BNLBox storage service.

scholarly journals Blockchain and novel coronavirus: Towards preventing COVID-19 and future pandemics

2020 ◽  
Vol 2 (3) ◽  
pp. 215-218
Author(s):  
Amirul Azim ◽  
◽  
Muhammad Nazrul Islam ◽  
Paul E. Spranger ◽  
◽  
...  
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Storage System ◽  
Data Management System ◽  
The Novel ◽  
Centralized Control ◽  
Novel Technology ◽  
Distributed Ledger ◽  
Novel Coronavirus ◽  
Present World

The present world has observed the SARS-CoV2 or COVID-19 spreading rapidly with a rising death toll and transmission rates with an absence of proper data management and information sharing. The current traditional database storage system has the limitations of a centralized control system and tampering of data, particularly when it is being shared with others. The Novel technology known as “Blockchain” is a distributed ledger technology that acts as a shared database, keeping all its copies synced and verified. The objective of this article is to study the concept of a Blockchain based pandemic data management system that would ensure unified patients’ data storage and reliable data management to trackdown coronavirus to combat against this and future pandemics.

scholarly journals Secure Content De-Duplication Utilizing Efficient Content Discovery and Preserving De-Duplication (Ecdpd)

2019 ◽  
Vol 8 (12S) ◽  
pp. 986-990
Keyword(s):  
Access Control ◽  
Data Storage ◽  
Cloud Storage ◽  
Storage System ◽  
Data Access ◽  
Data File ◽  
Data Deduplication ◽  
Efficient Technology ◽  
Data Access Control ◽  
Content Discovery

Cloud computing, an efficient technology that utilizes huge amount of data file storage with security. However, the content owner does not controlling data access for unauthorized clients and does not control data storage and usage of data. Some previous approaches data access control to help data de-duplication concurrently for cloud storage system. Encrypted data for cloud storage is not effectively handled by current industrial de-duplication solutions. The deduplication is unguarded from brute-force attacks and fails in supporting control of data access .An efficient data confining technique that eliminates redundant data’s multiple copies which is commonly used is Data-Deduplication. It reduces the space needed to store these data and thus bandwidth is saved. An efficient content discovery and preserving De-duplication (ECDPD) algorithm that detects client file range and block range of de-duplication in storing data files in the cloud storage system was proposed to overpower the above problems.Data access control is supported by ECDPD actively. Based on Experimental evaluations, proposed ECDPD method reduces 3.802 milliseconds of DUT (Data Uploading Time) and 3.318 milliseconds of DDT (Data Downloading Time) compared than existing approaches

scholarly journals Data management pipeline for plant phenotyping in a multisite project

2012 ◽  
Vol 39 (11) ◽  
pp. 948 ◽  
Author(s):  
Kenny Billiau ◽  
Heike Sprenger ◽  
Christian Schudoma ◽  
Dirk Walther ◽  
Karin I. Köhl
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Data Exchange ◽  
Data Access ◽  
Data Management System ◽  
Plant Phenotyping ◽  
Data Types ◽  
File Server ◽  
Management Concepts ◽  
Term Basis

In plant breeding, plants have to be characterised precisely, consistently and rapidly by different people at several field sites within defined time spans. For a meaningful data evaluation and statistical analysis, standardised data storage is required. Data access must be provided on a long-term basis and be independent of organisational barriers without endangering data integrity or intellectual property rights. We discuss the associated technical challenges and demonstrate adequate solutions exemplified in a data management pipeline for a project to identify markers for drought tolerance in potato. This project involves 11 groups from academia and breeding companies, 11 sites and four analytical platforms. Our data warehouse concept combines central data storage in databases and a file server and integrates existing and specialised database solutions for particular data types with new, project-specific databases. The strict use of controlled vocabularies and the application of web-access technologies proved vital to the successful data exchange between diverse institutes and data management concepts and infrastructures. By presenting our data management system and making the software available, we aim to support related phenotyping projects.

scholarly journals PetaShare: A Reliable, Efficient and Transparent Distributed Storage Management System

2011 ◽  
Vol 19 (1) ◽  
pp. 27-43
Author(s):  
Tevfik Kosar ◽  
Ismail Akturk ◽  
Mehmet Balman ◽  
Xinqi Wang
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Management System ◽  
Distributed Storage ◽  
Storage System ◽  
Data Management System ◽  
Distributed Data ◽  
Distributed Data Storage ◽  
Data Movement ◽  
Reliability And Availability

Modern collaborative science has placed increasing burden on data management infrastructure to handle the increasingly large data archives generated. Beside functionality, reliability and availability are also key factors in delivering a data management system that can efficiently and effectively meet the challenges posed and compounded by the unbounded increase in the size of data generated by scientific applications. We have developed a reliable and efficient distributed data storage system, PetaShare, which spans multiple institutions across the state of Louisiana. At the back-end, PetaShare provides a unified name space and efficient data movement across geographically distributed storage sites. At the front-end, it provides light-weight clients the enable easy, transparent and scalable access. In PetaShare, we have designed and implemented an asynchronously replicated multi-master metadata system for enhanced reliability and availability, and an advanced buffering system for improved data transfer performance. In this paper, we present the details of our design and implementation, show performance results, and describe our experience in developing a reliable and efficient distributed data management system for data-intensive science.

scholarly journals A Symmetric Key Based Deduplicatable Proof of Storage for Encrypted Data in Cloud Storage Environments

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Cheolhee Park ◽  
Hyunil Kim ◽  
Dowon Hong ◽  
Changho Seo
Keyword(s):  
Cloud Storage ◽  
Service Providers ◽  
Random Oracle Model ◽  
Data Access ◽  
Random Oracle ◽  
Dictionary Attack ◽  
Outsourced Data ◽  
Cloud Storage Service ◽  
Storage Service ◽  
Symmetric Key

Over the recent years, cloud storage services have become increasingly popular, where users can outsource data and access the outsourced data anywhere, anytime. Accordingly, the data in the cloud is growing explosively. Among the outsourced data, most of them are duplicated. Cloud storage service providers can save huge amounts of resources via client-side deduplication. On the other hand, for safe outsourcing, clients who use the cloud storage service desire data integrity and confidentiality of the outsourced data. However, ensuring confidentiality and integrity in the cloud storage environment can be difficult. Recently, in order to achieve integrity with deduplication, the notion of deduplicatable proof of storage has emerged, and various schemes have been proposed. However, previous schemes are still inefficient and insecure. In this paper, we propose a symmetric key based deduplicatable proof of storage scheme, which ensures confidentiality with dictionary attack resilience and supports integrity auditing based on symmetric key cryptography. In our proposal, we introduce a bit-level challenge in a deduplicatable proof of storage protocol to minimize data access. In addition, we prove the security of our proposal in the random oracle model with information theory. Implementation results show that our scheme has the best performance.

Fast and Efficient Cloud Data Utilization with Deduplication

2018 ◽  
Vol 6 (6) ◽  
pp. 68
Author(s):  
Sunil S ◽  
A Ananda Shankar
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Storage System ◽  
Data Access ◽  
Data Deduplication ◽  
Cloud Data ◽  
Web Log ◽  
File Storage ◽  
Data Access Control ◽  
The Web

Cloud storage system is to provides facilitative file storage and sharing services for distributed clients.The cloud storage preserve the privacy of data holders by proposing a scheme to manage encrypted data storage with deduplication. This process can flexibly support data sharing with deduplication even when the data holder is offline, and it does not intrude the privacy of data holders. It is an effective approach to verify data ownership and check duplicate storage with secure challenge and big data support. We integrate cloud data deduplication with data access control in a simple way, thus reconciling data deduplication and encryption.We prove the security and assess the performance through analysis and simulation. The results show its efficiency, effectiveness and applicability.In this proposed system the upload data will be stored on the cloud based on date.This means that it has to be available to the data holder who need it when they need it. The web log record represents whether the keyword is repeated or not. Records with only repeated search data are retained in primary storage in cloud. All the other records are stored in temporary storage server. This step reduces the size of the web log thereby avoids the burden on the memory and speeds up the analysis.

Design of Smart Healthcare Data Management System Based on Hadoop

2014 ◽  
Vol 998-999 ◽  
pp. 1121-1124 ◽  
Author(s):  
Min Zhang ◽  
Ren Zhang ◽  
Cheng Sheng Liu
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Management System ◽  
Cloud Storage ◽  
Low Cost ◽  
Structural Data ◽  
Data Management System ◽  
Traditional Management ◽  
Healthcare Data ◽  
Smart Healthcare

This paper describes a smart healthcare data management system based on hadoop. Aiming at the disadvantage of Traditional management of medical data such as the increasing cost of consumption and the limited availability of the data, the smart healthcare data management system in this paper introduces a hybrid storage architecture including designs of Structured data storage which supported by RDBMS and Non-structural data storage which supported by Hadoop. This smart healthcare data management system has the advantages of low-cost, high fault tolerance, and scalability, and builds a cloud storage platform applied in the system of smart healthcare.

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