• DocumentCode
    2365016
  • Title

    Weight based dominating set clustering algorithm for small satellite networks

  • Author

    Qin, Jing ; Mao, Xiang ; McNair, Janise

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    3195
  • Lastpage
    3199
  • Abstract
    Due to the size and density of small satellite networks (SSNs), the traditional clustering algorithms of large monolithic satellite networks are often limited. This paper proposes a novel distributed weight-based dominating set clustering algorithm to address the clustering problems in the stochastically deployed SSNs. Considering the unique features of small satellites, this algorithm is able to form the clusters efficiently and stably. In this algorithm, satellites are separated into different groups according to their spatial characteristics. Firstly, a minimum dominating set is chosen as the candidate cluster head set based on their weight, which is a weighted combination of residual energy and connection degree. Then the cluster heads admit new neighbors that accept their invitations into the cluster, until the maximum cluster size is reached. Evaluated by the simulation results, in a SSN with 200 to 800 nodes, the algorithm is able to efficiently cluster more than 90% of nodes in 3 seconds.
  • Keywords
    artificial satellites; pattern clustering; satellite communication; set theory; SSN deployment; candidate cluster head set; monolithic satellite network; residual energy; small satellite network; spatial characteristics; stochastic process; weight based dominating set clustering algorithm; Aerospace electronics; Algorithm design and analysis; Clustering algorithms; Orbits; Satellite broadcasting; Satellites; Space vehicles; clustering; dominating set; small satellite network; weight;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2012 IEEE International Conference on
  • Conference_Location
    Ottawa, ON
  • ISSN
    1550-3607
  • Print_ISBN
    978-1-4577-2052-9
  • Electronic_ISBN
    1550-3607
  • Type

    conf

  • DOI
    10.1109/ICC.2012.6363792
  • Filename
    6363792