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Tytuł artykułu

Fair resource allocation schemes and network dimensioning problems

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Resource allocation problems are concerned with the allocation of limited resources among competing activities so as to achieve the best overall performances of the system but providing fair treatment of all the competitors. Telecommunication networks are facing the increasing demand for Internet services. Therefore, a problem of network dimensioning with elastic traffic arises which requires to allocate bandwidth to maximize service flows with fair treatment of all the services. In such applications, the so-called max-min fairness (MMF) solution concept is widely used to formulate the resource allocation scheme. This guarantees the fairness but may lead to significant losses in the overall throughput of the network. In this paper we show how multiple criteria optimization concepts can be used to generate various fair resource allocation schemes. The solution concepts are tested on the network dimensioning problem and their abilities to model various preferences are demonstrated.
Rocznik
Tom
Strony
34--42
Opis fizyczny
Bibliogr. 20 poz., tab., rys.
Twórcy
autor
  • Institute of Control and Computation Engineering, Warsaw University of Technology
  • Institute of Control and Computation Engineering Warsaw University of Technology Nowowiejska st 15/19 00-665 Warsaw, Poland
  • Polish-Japanese Institute of Information Technology Koszykowa st 86 02-008 Warsaw, Poland
Bibliografia
  • [1] D. Bertsekas and R. Gallager, Data Networks. Englewood Cliffs: Prentice-Hall, 1987.
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  • [7] M. M. Kostreva and W. Ogryczak, “Linear optimization with multiple equitable criteria”, RAIRO Oper. Res., vol. 33, pp. 275–297, 1999.
  • [8] H. Luss, “On equitable resource allocation problems: a lexicographic minimax approach”, Oper. Res., vol. 47, pp. 361–378, 1999.
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  • [11] P. Nilsson and M. Pióro, “Solving dimensioning problems for proportionally fair networks carrying elastic traffic”, Lund Institute of Technology at Lund University, 2002.
  • [12] W. Ogryczak, “Comments on properties of the minimax solutions In goal programming”, Eur. J. Oper. Res., vol. 132, pp. 17–21, 2001.
  • [13] W. Ogryczak and T. Śliwiński, “On equitable approaches to resource allocation problems: the conditional minimax solution”, J. Telecommun. Inform. Technol., no. 3, pp. 40–48, 2002.
  • [14] W. Ogryczak and A. Tamir, “Minimizing the sum of the k lar gest functions in linear time”, Inform. Proc. Lett., vol. 85, pp. 117–122, 2003.
  • [15] J. Rawls, The Theory of Justice. Cambridge: Harvard University Press, 1971.
  • [16] A. Tomaszewski, “A polynomial algorithm for solving a general max-min fairness problem” in Proc. 2nd Pol.-Germ. Teletraff. Symp. PGTS, 2002, pp. 253-258.
  • [17] A. P. Wierzbicki, “A mathematical basis for satisficing decision making”, Math. Modell., vol. 3, pp. 391–405, 1982.
  • [18] A. P. Wierzbicki, M. Makowski, and J. Wessels, Eds., Model Based Decision Support Methodology with Environmental Applications.Dordrecht: Kluwer, 2000.
  • [19] R. R. Yager, “On ordered weighted averaging aggregation operators in multicriteria decision making”, IEEE Trans. Syst., Man Cybern., vol. 18, pp. 183–190, 1988.
  • [20] R. R. Yager, “On the analytic representation of the Leximin ordering and its application to flexible constraint propagation”, Eur. J. Oper. Res., vol. 102, pp. 176–192, 1997.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPS2-0021-0033
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