Abstract
Localization of sensors nodes is a key and fundamental issue in WSNs due to random deployment. In this paper, we propose a tree based clustering (TBC) multidimensional scaling algorithm for wireless sensor networks with the purpose of overcoming the shortage of classical MDS algorithms in its localization accuracy and computing complexity. Clustering is adopted to degrade the problem scale in our approach and a moderate number of common nodes between clusters are kept during clustering. Inner cluster local coordinates are calculated and then mapped into global coordinates according the tree structure formed by clustering. The simulations on MATLAB are conducted and the results show that the proposed algorithm has better localization coverage and higher accuracy than the traditional MDS based algorithms.
Supported by the National Natural Science Foundation of China under Grant No. 61379023.
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Dai, G., Miao, C., Li, Y., Mao, K., Chen, Q. (2015). Study on Tree-Based Clustering MDS Algorithm for Nodes Localization in WSNs. In: Sun, L., Ma, H., Fang, D., Niu, J., Wang, W. (eds) Advances in Wireless Sensor Networks. CWSN 2014. Communications in Computer and Information Science, vol 501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46981-1_17
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DOI: https://doi.org/10.1007/978-3-662-46981-1_17
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