1 research outputs found
Maximum Likelihood Coordinate Systems for Wireless Sensor Networks: from physical coordinates to topology coordinates
Many WSN protocols require the location coordinates of the sensor nodes, as
it is useful to consider the data collected by the sensors in the context of
the location from which they were collected. Thus, one of the major challenges
in WSNs is to determine the coordinates of sensors while minimizing the
hardware cost. To address this, numerous localization algorithms have been
proposed in the literature. However, outcomes of these algorithms are affected
by noise, fading, and interference. As a result, their levels of accuracy may
become unacceptable in complex environments that contain obstacles and
reflecting surfaces. The alternative is to use topological maps based only on
connectivity information. Since they do not contain information about physical
distances, however, they are not faithful representatives of the physical
layout. Thus, the primary goal of this research is to discover a topology map
that provides more accurate information about physical layouts. In doing so,
this research has resulted in four main contributions. First, a novel concept
Maximum-Likelihood Topology Map for RF WSNs is presented. This topology map
provides a more accurate physical representation, by using the probability of
packet reception. The second contribution is Millimetre wave Topology Map
calculation, which is a novel topology mapping algorithm based on maximum
likelihood estimation for millimetre wave WSNs. The third contribution is a
distributed algorithm being proposed to calculate the topology coordinates of
sensors by themselves as two algorithms above calculate centrally, which
requires time. Since a topology map contains significant non-linear
distortions, two WSN applications i.e. target searching and extremum seeking,
which use a proposed topology map to localize the sensors and perform its
specified task are presented as the final contribution of this dissertation