An intelligent file transfer optimization for poor network conditions

Ming Yan, Bo Zhang, Gang Zhao, Xiaohui Kuang, Lu Liu, Ruyun Zhang*

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

File transfer is based on the reliable TCP protocol. However, when the network is of poor quality, TCP-based transmission will still perform less effectively due to some reasons. Existing approaches mainly optimize file transmission by modifying network strategies or optimize transmission mechanism. But when network conditions cannot be selected or modified, a suitable parameter adjustment method would be needed. The experiments in this paper firstly perform TCP-based file transmission tests on a poor network condition and find two problems. Then, multiple tests were performed on multiple platforms to detect the conditions under which these problems occurred. Next, to address the issue and improve the transmission performance, we propose an intelligent optimization scheme. By adjusting the transmission parameters and adding policies, the scheme equips the intermediate parameters with intelligent self-adaptation capabilities. We also test and evaluate the performance of the intelligent scheme. The result shows that the file transfer under the new scheme not only basically avoids the target problems, but also reduces the practical upload time under poor network condition from the perspective of decreasing the number of retransmissions and reducing the failure rate.

源语言英语
主期刊名Security and Privacy in Social Networks and Big Data - 6th International Symposium, SocialSec 2020, Proceedings
编辑Yang Xiang, Zheli Liu, Jin Li
出版商Springer Science and Business Media Deutschland GmbH
234-244
页数11
ISBN(印刷版)9789811590306
DOI
出版状态已出版 - 2020
活动6th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2020 - Tianjin, 中国
期限: 26 9月 202027 9月 2020

出版系列

姓名Communications in Computer and Information Science
1298 CCIS
ISSN(印刷版)1865-0929
ISSN(电子版)1865-0937

会议

会议6th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2020
国家/地区中国
Tianjin
时期26/09/2027/09/20

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