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.
International Journal of Wireless Information Networks – Springer Journals
Published: Oct 25, 2017
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