論文

査読有り
2018年1月12日

Application specific traffic control using network virtualization node in large-scale disasters

Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
  • Tsumugi Tairaku
  • ,
  • Akihiro Nakao
  • ,
  • Shu Yamamoto
  • ,
  • Saneyasu Yamaguchi
  • ,
  • Masato Oguchi

2018-
開始ページ
4004
終了ページ
4009
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1109/BigData.2017.8258414
出版者・発行元
Institute of Electrical and Electronics Engineers Inc.

When the Great East Japan Earthquake occurred in 2011, the network connectivity was significantly degraded in the wide area due to the multiple network failures as well as the traffic congestion. When the network failures occurred in multiple areas, it was difficult to quickly recognize the entire network situation only using the network traffic monitor system. In our prior works, we found that SNS messages contain the useful information to recognize the big picture of the network failures and proposed the network control system using SNS messages to improve the quickness of the network recovery. As the another critical issue in case of a large-scale disaster, users could not obtain the emergency information due to the network disturbance because the current IP network is operated not being aware of the applications. Thus we propose the application specific traffic control system with failure detection function based on SNS message to prioritize the important application traffic in the event of the large-scale disaster. Based on a series of experiments, this paper shows the effectiveness of a system that detects connection failure based on social information and controls the network bandwidth for each application. Especially, we focus on application specific traffic control experiment. An automatic SDN control is performed with the network virtualization node FLARE having SDN extension capability as well as the network slicing capability. We perform the experiments to determine the type of application based on the traffic and perform bandwidth control for each application using real Internet applications.

リンク情報
DOI
https://doi.org/10.1109/BigData.2017.8258414
DBLP
https://dblp.uni-trier.de/rec/conf/bigdataconf/TairakuNYO17
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000428073703141&DestApp=WOS_CPL
URL
http://dblp.uni-trier.de/db/conf/bigdataconf/bigdataconf2017.html#conf/bigdataconf/TairakuNYO17
ID情報
  • DOI : 10.1109/BigData.2017.8258414
  • ISSN : 2639-1589
  • DBLP ID : conf/bigdataconf/TairakuNYO17
  • SCOPUS ID : 85047750958
  • Web of Science ID : WOS:000428073703141

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