Please use this identifier to cite or link to this item: http://dspace.azjhpc.org/xmlui/handle/123456789/10
Title: DATA MIGRATION FOR LARGE SCIENTIFIC DATASETS IN CLOUDS
Authors: Hajnal, Akos
Nagy, Eniko
Kacsuk, Peter
Marton, Istvan
Keywords: Data management;Data transfer;Data migration;Cloud storage
Issue Date: Jul-2018
Publisher: Azerbaijan Journal of High Performance Computing
Abstract: Transferring large data files between various storages including cloud storages is an important task both for academic and commercial users. This should be done in an efficient and secure way. The paper describes Data Avenue that fulfills all these conditions. Data Avenue can efficiently transfer large files even in the range of TerraBytes among storages having very different access protocols (Amazon S3, OpenStack Swift, SFTP, SRM, iRODS, etc.). It can be used in personal, organizational and public deployment with all the security mechanisms required for these usage configurations. Data Avenue can be used by a GUI as well as by a REST API. The papers describes in detail all these features and usage modes of Data Avenue and also provides performance measurement results proving the efficiency of the tool that can be accessed and used via several public web pages.
URI: http://localhost:8080/xmlui/handle/123456789/10
ISSN: 2616-6127
2617-4383
DOI: https://doi.org/10.32010/26166127.2018.1.1.66.86
Journal Title: Azerbaijan Journal of High Performance Computing
Volume: 1
Issue: 1
First page number: 66
Last page number: 86
Number of pages: 21
Appears in Collections:Azerbaijan Journal of High Performance Computing

Files in This Item:
File Description SizeFormat 
paper5.pdf2.21 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.