Analysis of Shortest Paths and Subscriber Line Lengths in Telecommunication Access Networks View Full Text


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Article Info

DATE

2010-03

AUTHORS

C. Gloaguen, F. Fleischer, H. Schmidt, V. Schmidt

ABSTRACT

We consider random geometric models for telecommunication access networks and analyse their serving zones which can be given, for example, by a class of so-called Cox–Voronoi tessellations (CVTs). Such CVTs are constructed with respect to locations of network components, the nucleii of their induced cells, which are scattered randomly along lines induced by a Poisson line process. In particular, we consider two levels of network components and investigate these hierarchical models with respect to mean shortest path length and mean subscriber line length, respectively. We explain point-process techniques which allow for these characteristics to be computed without simulating the locations of lower-level components. We sustain our results by numerical examples which were obtained through Monte Carlo simulations, where we used simulation algorithms for typical Cox–Voronoi cells derived in a previous paper. Also, briefly, we discuss tests of correctness of the implemented algorithms. Finally, we present a short outlook to possible extensions concerning multi-level models and iterated random tessellations. More... »

PAGES

15-47

References to SciGraph publications

  • 1996-03. Géométrie aléatoire et architecture de réseaux in ANNALS OF TELECOMMUNICATIONS
  • 2005-12. Simulation of typical Cox–Voronoi cells with a special regard to implementation tests in MATHEMATICAL METHODS OF OPERATIONS RESEARCH
  • 2000. Stochastische Geometrie in NONE
  • 1977. Processus ponctuels in ECOLE D’ETÉ DE PROBABILITÉS DE SAINT-FLOUR VI-1976
  • 2001-10. Aggregate and fractal tessellations in PROBABILITY THEORY AND RELATED FIELDS
  • 2005-06. Approximations of functionals of some modulated-Poisson Voronoi tessellations with applications to modeling of communication networks in JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS
  • 1999. Introduction to Stochastic Networks in NONE
  • 2006-04. Fitting of stochastic telecommunication network models via distance measures and Monte–Carlo tests in TELECOMMUNICATION SYSTEMS
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    http://scigraph.springernature.com/pub.10.1007/s11067-007-9021-z

    DOI

    http://dx.doi.org/10.1007/s11067-007-9021-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1047932634


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