• DocumentCode
    2696102
  • Title

    Optimizing link weight in OSPF routing under unknown traffic matrices

  • Author

    Cheng, Xiao-mei ; Wang, Sheng ; Wang, Xiong

  • Author_Institution
    Key Lab. of Broadband Opt. Fiber Transm. & Commun. Networks, Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2009
  • fDate
    20-23 Oct. 2009
  • Firstpage
    340
  • Lastpage
    343
  • Abstract
    An important traffic engineering problem for OSPF networks is the determination of optimal link weights. In this paper, we assume that the traffic matrix, which specifies traffic load between every source-destination pair in the network, is unknown and varies with time, but that always lies inside an explicitly defined region. Our goal is to compute an optimal link weights that minimizes maximum link utilization for all traffic matrices inside the bounding region. We first present a mixed-integer programming formulation to compute the optimal link weights. We then present a heuristic algorithm to find the optimal weights. Our simulations show that the proposed algorithm not only performs better than existing weight setting schemes in terms of minimizing congestion ratio, but also can achieve solution which is close to the optimal solutions.
  • Keywords
    integer programming; routing protocols; telecommunication traffic; OSPF routing; maximum link utilization; mixed-integer programming formulation; open shortest path first routing; optimal link weights; source-destination pair; traffic engineering problem; unknown traffic matrices; Communication networks; Computer networks; Cost function; Genetic algorithms; Heuristic algorithms; Laboratories; Optical fibers; Routing protocols; Telecommunication traffic; Traffic control; Link Weight; OSPF Networks; Traffic Engineering; Uncertain Traffic Matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Local Computer Networks, 2009. LCN 2009. IEEE 34th Conference on
  • Conference_Location
    Zurich
  • Print_ISBN
    978-1-4244-4488-5
  • Electronic_ISBN
    978-1-4244-4487-8
  • Type

    conf

  • DOI
    10.1109/LCN.2009.5355109
  • Filename
    5355109