• DocumentCode
    266094
  • Title

    Flow aggregation for traffic engineering

  • Author

    Kamiyama, Noriaki ; Takahashi, Yousuke ; Ishibashi, Keisuke ; Shiomoto, Kohei ; Otoshi, Tatsuya ; Ohsita, Yuichi ; Murata, Masayuki

  • Author_Institution
    Osaka Univ., Suita, Japan
  • fYear
    2014
  • fDate
    8-12 Dec. 2014
  • Firstpage
    1936
  • Lastpage
    1941
  • Abstract
    Although the use of software-defined networking (SDN) enables routes of packets to be controlled with finer granularity (down to the individual flow level) by using traffic engineering (TE) and thereby enables better balancing of the link loads, the corresponding increase in the number of states that need to be managed at routers and controller is problematic in large-scale networks. Aggregating flows into macro flows and assigning routes by macro flow should be an effective approach to solving this problem. However, when macro flows are constructed as TE targets, variations of traffic rates in each macro flow should be minimized to improve route stability. We propose two methods for generating macro flows: one is based on a greedy algorithm that minimizes the variation in rates, and the other clusters micro flows with similar traffic variation patterns into groups and optimizes the traffic ratio of extracted from each cluster to aggregate into each macro flow. Evaluation using traffic demand matrixes for 48 hours of Internet2 traffic demonstrated that the proposed methods can reduce the number of TE targets to about 1/50 ~ 1/400 without degrading the link-load balancing effect of TE.
  • Keywords
    IP networks; greedy algorithms; resource allocation; software defined networking; telecommunication links; telecommunication network routing; Internet2 traffic; SDN; TE target reduction; flow aggregation; greedy algorithm; large-scale networks; link load balancing; microflow clusters; packets route control; route assignment; route stability improvement; software-defined networking; traffic demand matrixes; traffic engineering; traffic rate variation minimization; traffic ratio optimization; traffic variation patterns; Aggregates; Greedy algorithms; Next generation networking; Radio frequency; Reactive power; Routing protocols; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Communications Conference (GLOBECOM), 2014 IEEE
  • Conference_Location
    Austin, TX
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2014.7037091
  • Filename
    7037091