• DocumentCode
    3055025
  • Title

    Unsorting the Proportional Fairness Relation

  • Author

    Köppen, Mario ; Yoshida, Kaori ; Tsuru, Masato

  • Author_Institution
    Kyushu Inst. of Technol., Kitakyushu, Japan
  • fYear
    2011
  • fDate
    Nov. 30 2011-Dec. 2 2011
  • Firstpage
    47
  • Lastpage
    52
  • Abstract
    Typical problems related to the application of proportional fairness are sparsity of the relation with increasing dimension, and the operator confusion problem. Here, we propose a new fairness relation derived from proportional fairness to handle these problems. The design principle behind this relation is relational unsorting: if there is a relation x(R)y between elements x and y from n-dimensional Euclidian space, the unsorted relation x(uR)y holds whenever there is a permutation x* of the elements of x for which x*(R)y holds. We apply this concept to proportional fairness, study the properties of the new relation, contrast with another relation based on over-sorting proportional fairness, and provide simulations to demonstrate the ease of ordered proportional fairness for meta-heuristic search.
  • Keywords
    sparse matrices; telecommunication networks; telecommunication traffic; meta-heuristic search; n-dimensional Euclidian space; operator confusion problem; over-sorting proportional fairness; permutation; proportional fairness relation; relational unsorting; sparsity; Mirrors; Monte Carlo methods; Mutual information; Optimization; Search problems; Sorting; Vectors; fairness; ordered proportional fairness; preference modelling; proportional fairness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networking and Collaborative Systems (INCoS), 2011 Third International Conference on
  • Conference_Location
    Fukuoka
  • Print_ISBN
    978-1-4577-1908-0
  • Type

    conf

  • DOI
    10.1109/INCoS.2011.159
  • Filename
    6132778