doi: 10.7763/IJET.2010.V2.114
Optimized Energy Efficient Localization Technique in Mobile Sensor Networks
J. Jasper Gnana Chandran
,
S. P. Victor
- Department of EEE, Francis Xavier Engineering College, Tirunelveli, Tamilnadu, India
Abstract
Localization is a problem which has been studied for many years and it is an unavoidable problem when dealing with the sensor nodes. Typically, in localization a target to be localized moves at random within the coverage of the sensor network. Current localization systems are using simplistic movement models and they do not consider energy consumption of sensor nodes. The problem considered in this paper is exploration of an unknown environment with the goal of finding the nodes at an unknown location(s) using location aware (LA) nodes. In this paper, a Particle Swarm Optimization (PSO) based energy efficient localization method is proposed. The localization is performed by learning movement patterns and their parameters such as Received Signal Strength (RSS) and angle of arrival (AoA) to guide LA nodes for locating target(s). Only a small number of sensors are activated to track and localize the target; while others are turned into sleep mode thus minimizing the energy consumption. The proposed method is evaluated on various mobility models and by the simulation results it is shown that our proposed method increases the accuracy of localization by minimizing estimation errors with reduced energy consumption and overhead.
Keywords
- angle of arrival (AoA)
- Localization
- Mobile Wireless Sensor Networks
- Particle Swarm Optimization
- Received Signal Strength (RSS)
How to Cite
J. Jasper Gnana Chandran and S. P. Victor, "Optimized Energy Efficient Localization Technique in Mobile Sensor Networks," International Journal of Engineering and Technology, vol. 2, no. 2, pp. 149-156, 2010. https://doi.org/ 10.7763/IJET.2010.V2.114
Copyright & License
Copyright © 2010 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).