A Novel Range Free Localization Algorithm in Wireless Sensor Networks Based on Connectivity and Genetic Algorithms

A Novel Range Free Localization Algorithm in Wireless Sensor Networks Based on Connectivity and... Noting the vital importance of localization using wireless sensor networks in real-world applications, many limitations of existing techniques urge us to seek more advanced localization algorithms. This paper presents a new range-free algorithm which takes advantages of genetic algorithms (GAs) to optimize multi-objective functions used in calculating an unknown position of normal node. The proposed algorithm, so far has improved the typical rage-free algorithms. It has good impact on the solving of localization problems with high accuracy. The first part illustrates typical based DV-hop localization algorithms. The principle of position estimation via genetic algorithms is introduced later. A proposed objective function to be optimized is defined in a next part, and its optimization based on GAs allows the unknown position’s computation. The new algorithm has been proved functional by theoretical analysis and simulation results. We have also proved the efficient performance of the proposed approach by comparing it to some state-of-the-art techniques. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Wireless Information Networks Springer Journals

A Novel Range Free Localization Algorithm in Wireless Sensor Networks Based on Connectivity and Genetic Algorithms

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Engineering; Electrical Engineering
ISSN
1068-9605
eISSN
1572-8129
D.O.I.
10.1007/s10776-017-0375-y
Publisher site
See Article on Publisher Site

Abstract

Noting the vital importance of localization using wireless sensor networks in real-world applications, many limitations of existing techniques urge us to seek more advanced localization algorithms. This paper presents a new range-free algorithm which takes advantages of genetic algorithms (GAs) to optimize multi-objective functions used in calculating an unknown position of normal node. The proposed algorithm, so far has improved the typical rage-free algorithms. It has good impact on the solving of localization problems with high accuracy. The first part illustrates typical based DV-hop localization algorithms. The principle of position estimation via genetic algorithms is introduced later. A proposed objective function to be optimized is defined in a next part, and its optimization based on GAs allows the unknown position’s computation. The new algorithm has been proved functional by theoretical analysis and simulation results. We have also proved the efficient performance of the proposed approach by comparing it to some state-of-the-art techniques.

Journal

International Journal of Wireless Information NetworksSpringer Journals

Published: Oct 25, 2017

References

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