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MDIS: A Node Localization Algorithm Based on Multi-region Division and Similarity Matching

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Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 917))

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Abstract

This paper proposes an improved localization algorithm called MDIS (Multi-Region Division In Shadow). The algorithm divides the traditional overlapping communication regions constructed by neighbor anchor nodes (nodes whose locations are known) into many subregions, and coordinates of centroid points in these subregions could be calculated. Furthermore, the algorithm establishes relation arrays of the unknown node to anchor nodes and centroid points to anchor nodes. Then the location of unknown nodes in subregions is determined by calculating the correlation coefficient of above relation arrays. And simulations demonstrate that MDIS algorithm increases the accuracy and stability compared to other range-free algorithms.

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References

  1. Chen, L., Xiong, X., Liu, K., et al.: POPA: localising nodes by splitting PLA with NTH-HOP anchor neighbours. Electron. Lett. 50(13), 964–966 (2014). https://doi.org/10.1049/el.2013.4046

    Article  Google Scholar 

  2. Rodriquez, R.Y., Julcapoma, M.R., Jacinto, R.A.: Network monitoring environmental quality in agriculture and pisciculture with low power sensor nodes based on ZigBee and GPRS technology. In: IEEE Xxiii International Congress on Electronics, Electrical Engineering and Computing, pp. 1–6. IEEE (2017). https://doi.org/10.0.4.85/INTERCON.2016.7815578

    Google Scholar 

  3. Qiang, R., Wang, W., Wang, H., et al.: 3D maximum likelihood estimation positioning algorithm based on RSSI ranging. In: Advanced Information Technology, Electronic and Automation Control Conference, pp. 1311–1314. IEEE (2017). https://doi.org/10.1109/IAEAC.2017.8054226

  4. Shahzad, F., Shaltami, T., Shakshukhi, E.: DV-maxHop: a fast and accurate range-free localization algorithm for anisotropic wireless networks. IEEE Trans. Mob. Comput. PP(99), 2494–2505 (2017). https://doi.org/10.1109/TMC.2016.2632715

    Article  Google Scholar 

  5. Simic, S.N., Sastry, S.: Distributed localization in wireless ad hoc networks (2001). https://doi.org/10.1145/1653760.1653768

  6. Niculescu, D., Nath, B.: DV based positioning in ad hoc networks. Telecommun. Syst. 22(1–4), 267–280 (2003). https://doi.org/10.1023/A:1023403323460

    Article  Google Scholar 

  7. He, T., Huang, C., Blum, B.M., et al.: Range-free localization schemes for large scale sensor networks. In: International Conference on Mobile Computing and Networking, pp. 81–95. ACM (2005)

    Google Scholar 

  8. Kim, K.Y., Shin, Y.: A distance boundary with virtual nodes for the weighted centroid localization algorithm. Sensors 18(4), 1054 (2018). https://doi.org/10.3390/s18041054

    Article  Google Scholar 

  9. Wei, L., Zhou, B., Ma, X., et al.: Lightning: a high-efficient neighbor discovery protocol for low duty cycle WSNs. IEEE Commun. Lett. 20(5), 966–969 (2016). https://doi.org/10.1109/LCOMM.2016.2536018

    Article  Google Scholar 

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Acknowledgements

This paper is supported by the NNSFC (grant number 61373091); Civil Aviation Airport United Laboratory of Second Research Institute, CAAC&& Sichuan University of Chengdu (grant number 2015-YF04-00050-JH); the Collaborative Innovation of Industrial Cluster Project of Chengdu (grant number 2016-XT00-00015-GX); NNSFC&CAAC U1533203; the key Technology R&D program of Sichuan Province (grant number 2016GZ0068).

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Authors and Affiliations

  1. School of Computer Science, Sichuan University, Chengdu, China

    Hao Wang, Haixiang Chen & Liangyin Chen

  2. School of Mathematics and Information Engineering, Chongqing University of Education, Chongqing, China

    Ping Yuan

  3. School of Computer Science and Technology, Southwest University for Nationalities, Chengdu, China

    Feng Yin

  4. The Second Research Institute, General Administration of Civil Aviation of China, Chengdu, China

    Qian Luo

Authors
  1. Hao Wang
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  2. Haixiang Chen
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  3. Ping Yuan
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  4. Feng Yin
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  5. Qian Luo
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  6. Liangyin Chen
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Corresponding author

Correspondence to Liangyin Chen .

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Editors and Affiliations

  1. Shandong University, Jinan, China

    Yuqing Sun

  2. Fudan University, Shanghai, China

    Tun Lu

  3. Guilin University of Technology, Guilin, China

    Xiaolan Xie

  4. University of Shanghai for Science and Technology, Shanghai , China

    Liping Gao

  5. Tongji University, Shanghai, China

    Hongfei Fan

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Wang, H., Chen, H., Yuan, P., Yin, F., Luo, Q., Chen, L. (2019). MDIS: A Node Localization Algorithm Based on Multi-region Division and Similarity Matching. In: Sun, Y., Lu, T., Xie, X., Gao, L., Fan, H. (eds) Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2018. Communications in Computer and Information Science, vol 917. Springer, Singapore. https://doi.org/10.1007/978-981-13-3044-5_40

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  • DOI: https://doi.org/10.1007/978-981-13-3044-5_40

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-3043-8

  • Online ISBN: 978-981-13-3044-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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