• DocumentCode
    2522115
  • Title

    Exponential random geometric graph process models for mobile wireless networks

  • Author

    Shang, Yilun

  • Author_Institution
    Dept. of Math., Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    56
  • Lastpage
    61
  • Abstract
    In this paper, we consider a one-dimensional random geometric graph process with the inter-nodal gaps evolving according to an exponential first order autoregressive (AR(1)) process. The transition probability matrix and stationary distribution are derived for the Markov chains in terms of network connectivity and the number of components. We characterize an algorithm for the hitting time regarding disconnectivity. In addition, we also study static topological properties including connectivity, degree distributions and the largest nearest neighbor distance associated with the random graph process. Both closed form results and limit theorems are provided.
  • Keywords
    Markov processes; radio networks; 1D random geometric graph process; Markov chains; disconnectivity; exponential first order autoregressive process; exponential random geometric graph process model; inter-nodal gaps; mobile wireless networks; nearest neighbor distance; network connectivity; random graph process; stationary distribution; transition probability matrix; Analytical models; Autoregressive processes; Joining processes; Mathematical model; Mathematics; Nearest neighbor searches; Probability distribution; Solid modeling; Wireless networks; Wireless sensor networks; autoregressive process; component; connectivity; mobile network; random geometric graph;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cyber-Enabled Distributed Computing and Knowledge Discovery, 2009. CyberC '09. International Conference on
  • Conference_Location
    Zhangijajie
  • Print_ISBN
    978-1-4244-5218-7
  • Electronic_ISBN
    978-1-4244-5219-4
  • Type

    conf

  • DOI
    10.1109/CYBERC.2009.5342212
  • Filename
    5342212