Using Micro-Genetic Algorithms to Improve Localization in Wireless Sensor Networks

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)...

• Type: Journal
• Year: 2006
• Where: JCM
• Authors: Vincent Tam, King-Yip Cheng, King-Shan Lui
• Keywords: JCM 2006, Localization Methods, Optimization Problems, Position Estimation