Modified MDS-MAP Localization Algorithm with Distance Error Correction in Energy Clustering Wireless Sensor Networks

TIAN Hongliang; QIAN Zhihong; WANG Yijun; LIANG Xiao

doi:10.11999/JEIT161237

Volume 39 Issue 7

Jul. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(7): 1735-1740

TIAN Hongliang, QIAN Zhihong, WANG Yijun, LIANG Xiao. Modified MDS-MAP Localization Algorithm with Distance Error Correction in Energy Clustering Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2017, 39(7): 1735-1740. doi: 10.11999/JEIT161237

Citation:

TIAN Hongliang, QIAN Zhihong, WANG Yijun, LIANG Xiao. Modified MDS-MAP Localization Algorithm with Distance Error Correction in Energy Clustering Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2017, 39(7): 1735-1740. doi: 10.11999/JEIT161237

Citation:

TIAN Hongliang, QIAN Zhihong, WANG Yijun, LIANG Xiao. Modified MDS-MAP Localization Algorithm with Distance Error Correction in Energy Clustering Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2017, 39(7): 1735-1740. doi: 10.11999/JEIT161237

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Modified MDS-MAP Localization Algorithm with Distance Error Correction in Energy Clustering Wireless Sensor Networks

doi: 10.11999/JEIT161237

1.
2.
(School of Communication Engineering, Jilin University, Changchun 130012, China)

Funds:

The National Natural Science Foundation of China (61371092, 61540022)

Received Date: 2016-11-14
Rev Recd Date: 2017-04-05
Publish Date: 2017-07-19

Abstract

Abstract

The classical MDS-MAP algorithm has the disadvantage of large error and the computational complexity increases sharply with the increase of network size in the localization of wireless sensor networks. The clustering method based on the residual energy of the neighbor nodes is designed. The cluster has the proper node degree and cluster size, which reduces the calculation amount and error of the next-step localization algorithm. Then, for the intra-cluster nodes with only connectivity information, the distance between the sink and other single-hop nodes is obtained using the time difference ranging method. A multi-hop distance error correction algorithm is proposed. The distance between nodes in a cluster is obtained using the geometrical relationship of neighboring nodes and the node connectivity. Multi-Dimensional Scaling (MDS) is used to calculate the relative coordinates of nodes in each cluster, and the inter-cluster coordinates are merged and converted into absolute coordinates by the anchor nodes. Finally, the localization of the nodes is realized. The proposed method provides more accurate information of inter-node distance based on energy clustering and multi-hop interval weighted geometric distance correction algorithm. Compared with classical MDS algorithm, this method can further improve the positioning accuracy and reduce the power consumption of wireless sensor network localization.
- Wireless sensor networks,
- Localization,
- Multi-Dimensional Scaling (MDS),
- Clustering,
- Distance error correction

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References(19)

References

钱志鸿, 王义君. 面向物联网的无线传感器网络综述[J]. 电子与信息学报, 2013, 35(1): 215-227. doi: 10.3724/SP.J.1146. 2012.00876.

QIAN Zhihong and WANG Yijun. Internet of Things- oriented wireless sensor networks review[J]. Journal of Electronics Information Technology, 2013, 35(1): 215-227. doi: 10.3724/SP.J.1146.2012.00876.

钱志鸿, 王义君. 物联网技术与应用研究[J]. 电子学报, 2012, 40(5): 1023-1029. doi: 10.3969/j.issn.0372-2112.2012.05.026.

QIAN Zhihong and WANG Yijun. IoT technology and application[J]. Acta Electronica Sinica, 2012, 40(5): 1023-1029. doi: 10.3969/j.issn.0372-2112.2012.05.026.

WU C, MU Q, ZHANG Z, et al. Indoor positioning system based on inertial MEMS sensors: Design and realization[C]. 2016 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), Chengdu, 2016: 370-375. doi: 10.1109/CYBER.2016. 7574852.

李建坡, 钟鑫鑫, 徐纯. 无线传感器网络静态节点定位算法综述[J]. 东北电力大学学报, 2015, 35(2): 73-82.

LI Jianpo, ZHONG Xinxin, and XU Chun. Static wireless sensor network node localization algorithm review[J]. Journal of Northeast Dianli University, 2015, 35(2): 73-82.

MU L, QU X, and ZHOU Z. SARL: A flexible simulation architecture of range-based location in WSN[C]. The 35th Chinese Control Conference (CCC), Chengdu, 2016: 8412-8417. doi: 10.1109/ChiCC.2016.7554698.

GOLESTANIAN M and POELLABAUER C. Localization in heterogeneous wireless sensor networks using elliptical range estimation[C]. 2016 International Conference on Computing, Networking and Communications, Kauai, 2016: 1-7. doi: 10.1109/ICCNC.2016.7440701.

KARBASI A and OH S. Robust localization from incomplete local information[J]. IEEE/ACM Transactions on Networking, 2013, 21(4): 1131-1144. doi: 10.1109/TNET. 2012.2220378.

AMAR A, WANG Y, and LEUS G. Extending the classical multidimensional scaling algorithm given partial pairwise distance measurements[J]. IEEE Signal Processing Letters, 2010, 17(5): 473-476. doi: 10.1109/LSP.2010.2043890.

CHAN F K W and SO H C. Efficient weighted multidimensional scaling for wireless sensor network localization[J]. IEEE Transactions on Signal Processing, 2009, 57(11): 4548-4553. doi: 10.1109/TSP.2009.2024869.

罗莉琼, 罗娟. 多维标度定位算法研究[J]. 信息技术, 2011, 35(4): 6364. doi: 10.13274/j.cnki.hdzj.2011.04.020.

LUO Liqiong and LUO Juan. Research on multi-dimension scaling algorithm[J]. Information Technology, 2011, 35(4): 63-64. doi: 10.13274/j.cnki.hdzj.2011.04.020.

马震, 刘云, 沈波. 分布式无线传感器网络定位算法MDS- MAP(D)[J]. 通信学报, 2008, 29(6): 57-62.

MA Zhen, LIU Yun, and SHEN Bo. Distributed locating algorithm for wireless sensor networks-MDS-MAP(D)[J]. Journal on Communications, 2008, 29(6): 57-62.

HERGET C J and FRAZER J W. Applications of modern control theory to process control[J]. 1979 18th IEEE Conference on Decision and Control Including the Symposium on Adaptive Processes, Lauderdale Florida, 1979, 2: 905-906.

傅菊平, 齐小刚. 基于剩余能量和节点度的无线传感器网络分簇算法[J]. 计算机应用研究, 2011, 28(1): 250-252. doi: 10.3969/j.issn.1001-3695.2011.01.070.

FU Juping and QI Xiaogang. Clustering algorithm based on residual energy and node degree for WSNs[J]. Application Research of Computers, 2011, 28(1): 250-252. doi: 10.3969/ j.issn.1001-3695.2011.01.070.

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