Title: An efficient data transfer service for scientific applications in cloud environments

Authors: Ying Hu; Changsong Liu

Addresses: College of Computer and Communication, Hunan Institute of Engineering, Xiangtan, 411104, China ' Department of Computer Science, Hunan Institute of Engineering, Xiangtan City, China

Abstract: Recently, more and more data-intensive scientific applications have been deployed in cloud environments. Therefore, how to improve the efficiency of data transfer becomes an important issued that needs to be addressed. In this paper, we present an efficient data transfer framework which provides an integrated platform for data transfer, data scheduling and performance monitoring. Unlike those existing studies that focus on the utilisation of bandwidth resources, the proposed framework is implemented by integrating data transfer service and data scheduling service through a performance prediction service. In this way, it provides a flexible mechanism to enable a cloud system to improve the efficiency of data transfer. The implementation of the proposed framework has been deployed in a real-world cloud system, and experimental results have shown that in can significantly improve the efficiency of massive-data transfer comparing with many existing approaches.

Keywords: cloud computing; data transfer; data scheduler; performance prediction.

DOI: 10.1504/IJNVO.2019.103419

International Journal of Networking and Virtual Organisations, 2019 Vol.21 No.3, pp.289 - 306

Received: 15 May 2017
Accepted: 07 Sep 2017
Published online: 06 Nov 2019 *

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