{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:57:35Z","timestamp":1760241455305,"version":"build-2065373602"},"reference-count":24,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,4,16]],"date-time":"2018-04-16T00:00:00Z","timestamp":1523836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>The rapid transfer of massive data in the cloud environment is required to prepare for unexpected situations like disaster recovery. With regard to this requirement, we propose a new approach to transferring cloud virtual machine images rapidly in the cloud environment utilizing dedicated Data Transfer Nodes (DTNs). The overall procedure is composed of local\/remote copy processes and a DTN-to-DTN transfer process. These processes are coordinated and executed based on a fork system call in the proposed algorithm. In addition, we especially focus on the local copy process between a cloud controller and DTNs and improve data transfer performance through the well-tuned mount techniques in Network File System (NFS)-based connections. Several experiments have been performed considering the combination of synchronous\/asynchronous modes and the network buffer size. We show the results of throughput in all the experiment cases and compare them. Consequently, the best throughput in write operations has been obtained in the case of an NFS server in a DTN and an NFS client in a cloud controller running entirely in the asynchronous mode.<\/jats:p>","DOI":"10.3390\/sym10040110","type":"journal-article","created":{"date-parts":[[2018,4,16]],"date-time":"2018-04-16T03:12:09Z","timestamp":1523848329000},"page":"110","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Enhancing Data Transfer Performance Utilizing a DTN between Cloud Service Providers"],"prefix":"10.3390","volume":"10","author":[{"given":"Wontaek","family":"Hong","sequence":"first","affiliation":[{"name":"Division of National Supercomputing, Korea Institute of Science and Technology Information, Daejeon 34141, Korea"},{"name":"Department of Electrical and Computer Engineering, SungKyunKwan University, Suwon, Gyeonggi-do 16419, Korea"}]},{"given":"Jeonghoon","family":"Moon","sequence":"additional","affiliation":[{"name":"Division of National Supercomputing, Korea Institute of Science and Technology Information, Daejeon 34141, Korea"}]},{"given":"Woojin","family":"Seok","sequence":"additional","affiliation":[{"name":"Division of National Supercomputing, Korea Institute of Science and Technology Information, Daejeon 34141, Korea"}]},{"given":"Jinwook","family":"Chung","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, SungKyunKwan University, Suwon, Gyeonggi-do 16419, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.future.2008.07.014","article-title":"Special section: OptIPlanet\u2014The OptIPuter global collaboratory","volume":"25","author":"Smarr","year":"2009","journal-title":"Future Gener. 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