Abstract
Localization accuracy and low operating costs are substantial and key issues in operating and managing wireless sensor networks. The literature has many algorithms which used optimization techniques to promote the localization accuracy. This paper proposes a novel and an efficient algorithm based on state of art of black box optimization techniques, in order to promote the localization accuracy. This optimization technique is called hierarchical structure poly-particle swarm optimization. The proposed algorithm considers that the ranging technique is based on the cheapest distance estimation method which is receive signal strength indicator (RSSI). The proposed algorithm is more charming to promote the localization accuracy, where it has special characteristics such as the easy implementation of HSPPSO. In addition, RSSI is the cost efficiency measurement method. Simulation results demonstrate the effectiveness of the proposed algorithm comparing to other algorithms which based on optimization, e.g., ant colony, genetic algorithm, and basic PSO. This is clearly evident in some of the evaluation metrics such as localization accuracy, localization rate, and complexity.
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This work is partially supported by Program for the National Natural Science Foundation of China (61672220).
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Gumaida, B.F., Luo, J. An Efficient Algorithm for Wireless Sensor Network Localization Based on Hierarchical Structure Poly-Particle Swarm Optimization. Wireless Pers Commun 97, 125–151 (2017). https://doi.org/10.1007/s11277-017-4497-4
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DOI: https://doi.org/10.1007/s11277-017-4497-4