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Node localization algorithm of wireless sensor networks with mobile beacon node

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Abstract

When maximum movement distance of beacon node is limited, in order to improve the localization accuracy of sensor nodes, node localization algorithm of wireless sensor networks with mobile beacon node (NLA_MB) is proposed. NLA_MB algorithm divides the movement area of beacon node into some hexagonal grids, and establishes optimization model of node localization errors according to the movement path constraint, movement distance constraint and other constraints of beacon node. Beacon node uses heuristic method to solve the model approximately based on virtual force theory and location information of guide sensor nodes, and obtains a moving path which is suitable for the current node distribution. According to location information of beacon node or anchor sensor nodes, sensor nodes use maximum likelihood estimation algorithm to calculate their own location coordinates. Simulation results show that NLA_MB algorithm is suitable for the distribution scenarios of sensor nodes, such as full coverage distribution, L-type distribution, Tian-type distribution and U-type distribution. It can increase the number of sojourn locations of beacon node and average number of anchor points of sensor nodes, and reduce average localization error of sensor nodes. Under certain conditions, NLA_MB algorithm outperforms DOUBLE_SCAN, ZSCAN, MLE, RSCAN and DBMS algorithms.

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Acknowledgments

This work was supported by National Natural Science Foundation of China under Grant No.61501403, Zhejiang Provincial Natural Science Foundation of China under Grant No.LY15F030004, Zhejiang Provincial Public Welfare Technology Application and Research Project of China under Grant No.2016C33038 and No.2015C33028.

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Correspondence to Yourong Chen.

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Chen, Y., Lu, S., Chen, J. et al. Node localization algorithm of wireless sensor networks with mobile beacon node. Peer-to-Peer Netw. Appl. 10, 795–807 (2017). https://doi.org/10.1007/s12083-016-0522-8

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  • DOI: https://doi.org/10.1007/s12083-016-0522-8

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