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Localization Algorithm for Large Scale Wireless Sensor Networks Based on Fast-SVM

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Abstract

Sensor node localization is one of research hotspots in the applications of wireless sensor networks (WSNs) field. In recent years, many scholars proposed some localization algorithms based on machine learning, especially support vector machine (SVM). Localization algorithms based on SVM have good performance without pairwise distance measurements and special assisting devices. But if detection area is too wide and the scale of wireless sensor network is too large, the each sensor node needs to be classified many times to locate by SVMs, and the location time is too long. It is not suitable for the places of high real-time requirements. To solve this problem, a localization algorithm based on fast-SVM for large scale WSNs is proposed in this paper. The proposed fast-SVM constructs the minimum spanning by introducing the similarity measure and divided the support vectors into groups according to the maximum similarity in feature space. Each group support vectors is replaced by linear combination of “determinant factor” and “adjusting factor” which are decided by similarity. Because the support vectors are simplified by the fast-SVM, the speed of classification is evidently improved. Through the simulations, the performance of localization based on fast-SVM is evaluated. The results prove that the localization time is reduce about 48 % than existing localization algorithm based on SVM, and loss of the localization precision is very small. Moreover, fast-SVM localization algorithm also addresses the border problem and coverage hole problem effectively. Finally, the limitation of the proposed localization algorithm is discussed and future work is present.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China under Grant No. 61401083 and the Natural Science Foundation for Young Scholars of Hebei Province of China under Grant No. F2014501139.

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Authors and Affiliations

  1. School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Taishan Road 143, Qinhuangdao, 066004, Hebei, China

    Fang Zhu

  2. School of Resource and Material, Northeastern University at Qinhuangdao, Taishan Road 143, Qinhuangdao, 066004, Hebei, China

    Junfang Wei

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  1. Fang Zhu
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Correspondence to Fang Zhu.

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Zhu, F., Wei, J. Localization Algorithm for Large Scale Wireless Sensor Networks Based on Fast-SVM. Wireless Pers Commun 95, 1859–1875 (2017). https://doi.org/10.1007/s11277-016-3665-2

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  • DOI: https://doi.org/10.1007/s11277-016-3665-2

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