論文

査読有り 本文へのリンクあり
2018年2月

Separating predictable and unpredictable flows via dynamic flow mining for effective traffic engineering

IEICE Transactions on Communications
  • Yousuke Takahashi
  • ,
  • Keisuke Ishibashi
  • ,
  • Masayuki Tsujino
  • ,
  • Noriaki Kamiyama
  • ,
  • Kohei Shiomoto
  • ,
  • Tatsuya Otoshi
  • ,
  • Yuichi Ohsita
  • ,
  • Masayuki Murata

E101B
2
開始ページ
538
終了ページ
547
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
10.1587/transcom.2017EBT0001

© 2018 The Institute of Electronics, Information and Communication Engineers. To efficiently use network resources, internet service providers need to conduct traffic engineering that dynamically controls traffic routes to accommodate traffic change with limited network resources. The performance of traffic engineering (TE) depends on the accuracy of traffic prediction. However, the size of traffic change has been drastically increasing in recent years due to the growth in various types of network services, which has made traffic prediction difficult. Our approach to tackle this issue is to separate traffic into predictable and unpredictable parts and to apply different control policies. However, there are two challenges to achieving this: Dynamically separating traffic according to predictability and dynamically controlling routes for each separated traffic part. In this paper, we propose a macroflow-based TE scheme that uses different routing policies in accordance with traffic predictability. We also propose a trafficseparation algorithm based on real-time traffic analysis and a framework for controlling separated traffic with software-defined networking technology, particularly OpenFlow. An evaluation of actual traffic measured in an Internet2 network shows that compared with current TE schemes the proposed scheme can reduce the maximum link load by 34% (at the most congested time) and the average link load by an average of 11%.

リンク情報
DOI
https://doi.org/10.1587/transcom.2017EBT0001
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85041651888&origin=inward 本文へのリンクあり
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85041651888&origin=inward
ID情報
  • DOI : 10.1587/transcom.2017EBT0001
  • ISSN : 0916-8516
  • eISSN : 1745-1345
  • SCOPUS ID : 85041651888

エクスポート
BibTeX RIS