• DocumentCode
    1789205
  • Title

    A multi-attribute decision making approach to congestion control in delay tolerant networks

  • Author

    Kaimin Wei ; Song Guo ; Deze Zeng ; Ke Xu

  • Author_Institution
    State Key Lab. of Software Dev. Environ., Beihang Univ., Beijing, China
  • fYear
    2014
  • fDate
    10-14 June 2014
  • Firstpage
    2742
  • Lastpage
    2747
  • Abstract
    DTNs are prone to congestion due to limited resource on each node and unpredictable end-to-end delay. We aim to develop an effective congestion control mechanism in this paper. For this purpose, we first identify a list of major congestion factors by analyzing the causes of congestion. We then model the congestion control as a multiple attribute decision making problem (MADM), in which the weight of congestion factors is measured by an entropy method. To solve this problem, we present a MADM-based congestion control mechanism that determines a set of forwarding messages and its transmission order on each encounter event. Moreover, we design a buffer management scheme that deletes messages whose removal would incur the least impact to the network performance when the buffer overflows. Extensive real-trace driven simulation is conducted and the experimental results finally validate the efficiency of our proposed congestion control mechanism.
  • Keywords
    decision making; delay tolerant networks; electronic messaging; telecommunication congestion control; DTN end-to-end delay; MADM based congestion control mechanism; buffer overflow management scheme; delay tolerant networks; forwarding messages; messages deletes; messages transmission; multiple attribute decision making problem; Buffer storage; Decision making; Delays; Mobile communication; Peer-to-peer computing; Routing; Weight measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2014 IEEE International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/ICC.2014.6883739
  • Filename
    6883739