Abstract
Spatial deployment of signal sources affects performance of indoor positioning systems, thus has received more attentions in recent years. This paper presents a FWA method from fireworks algorithm, to provide the optimal deployment solution. Taking fine chromosomes as fireworks, the explosion factors are set including the number of explosion sparks and the radius of all explosion sparks. The supplemented individuals are produced from explosion and random generation, which helps increase the diversity of population and guarantee the qualities of individuals. After crossover and mutation, population evolves to the next generation. The optimal result from evolutions refers to a deployment solution, i.e., certain number of signal sources with their locations. The FWA algorithm has been tested to have good convergence ability by a series of experiments, with iBeacons based indoor positioning system in an underground parking lot and the fingerprint based indoor location method. Compared with the usually used optimization algorithms, FWA has the best searching ability in single-objective and multi-objective cases, and it obtains the best optimization result considering only positioning error, or both positioning error and the cost of iBeacons. Therefore, the proposed FWA provides optimal deployment of signal sources for indoor positioning systems.
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Acknowledgments
This work was supported by the National Key Research and Development Program of China (Project No. 2016YFB0502201).
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Zhao, J., Wen, S., Ai, H., Cai, B. (2018). Deployment Optimization of Indoor Positioning Signal Sources with Fireworks Algorithm. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11336. Springer, Cham. https://doi.org/10.1007/978-3-030-05057-3_18
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DOI: https://doi.org/10.1007/978-3-030-05057-3_18
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