Abstract
Wireless Sensor Network (WSN) consists of sensors with small volume and limited power. These sensors can communicate with each other and fuse data to make different decisions. Target tracking is an important application in wireless sensor network. How to schedule nodes for tracking the moving target and how to improve the tracking accuracy are the problems that we face. In this paper, we introduce a fuzzy tree system in target tracking. The fuzzy tree system is composed of two layers, in which the first one is to decide which nodes to move and the second one is to decide the distance and angle. All the parameters are tuned by the Cuckoo Search algorithm (CS). We performed a large number of simulations in choosing different numbers of the moving nodes. The results of my experimental data show that the adaptive fuzzy system has a good effect on target tracking, and the Cuckoo Search algorithm outperforms the algorithms widely used now in tuning the parameters.
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This work is supported by the National Natural Science Foundation of China (Grants No. 61731006).
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Xia, Q., Lin, J., Liu, Q., Leng, S. (2020). A Fuzzy Tree System Based on Cuckoo Search Algorithm for Target Tracking in Wireless Sensor Network. In: Chen, Y., Nakano, T., Lin, L., Mahfuz, M., Guo, W. (eds) Bio-inspired Information and Communication Technologies. BICT 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 329. Springer, Cham. https://doi.org/10.1007/978-3-030-57115-3_23
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