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Open Access Publications from the University of California

Statistical Model of Lossy Links in Wireless Sensor Networks

  • Author(s): Alberto Cerpa
  • Jennifer Wong
  • Louane Kuang
  • Miodrag Potkonjak
  • Deborah Estrin
  • et al.
Abstract

Recently, several landmark wireless sensor network deployment studies clearly demonstrated a great discrepancy between experimentally observed communication properties and properties produced by widely used simulation models. Our first goal is to provide sound foundations for conclusions drawn from these studies by extracting the relationship between pairs of location (e.g distance) and communication properties (e.g. reception rate) using non-parametric statistical techniques and by calculating intervals of confidence for all claims. Furthermore, we study not only individual links properties, but also their correlation with respect to common transmitters and receivers and their geometrical location. The second and main objective is to develop a series of wireless network generators which produce networks of an arbitrary size and under arbitrary deployment rules with realistic communication properties. For this task we use a generalized rejection algorithm and an iterative improvement-based optimization procedure to generate instances of the network that are statistically similar to empirically observed networks. We evaluate the accuracy our conclusions using the proposed model on a set of standard communication tasks, such as connectivity maintenance and routing.

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