ISSN : 1796-2021
Volume : 1    Issue : 4    Date : July 2006

Using Micro-Genetic Algorithms to Improve Localization in Wireless Sensor Networks
Vincent Tam, King-Yip Cheng and King-Shan Lui
Page(s): 1-10
Full Text:
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Wireless sensor networks are widely adopted in many location-sensitive applications including
disaster management, environmental monitoring, military applications where the precise
estimation of each node position is inevitably important when the absolute positions of a relatively
small portion as anchor nodes of the underlying network were predetermined. Intrinsically,
localization is an unconstrained optimization problem based on various distance/path measures.
Most of the existing localization methods focus on using different heuristic-based or mathematical
techniques to increase the precision in position estimation. However, there were recent studies
showing that nature-inspired algorithms like the ant-based or genetic algorithms can effectively
solve many complex optimization problems. In this paper, we propose to adapt an evolutionary
approach, namely a micro-genetic algorithm, as a post-optimizer into some existing localization
methods such as the Ad-hoc Positioning System (APS) to further improve the accuracy of their
position estimation. Obviously, our proposed MGA is highly adaptable and easily integrated into
other localization methods. Furthermore, the remarkable improvements attained by our proposed
MGA on both isotropic and anisotropic topologies of our simulation tests prompt for several
interesting directions for further investigation.

Index Terms
wireless sensor networks, localization, optimization techniques, heuristic search methods,
microgenetic algorithms, distance measures.