Computer Science ›› 2019, Vol. 46 ›› Issue (8): 145-151.doi: 10.11896/j.issn.1002-137X.2019.08.024

• Network & Communication • Previous Articles     Next Articles

Advanced MDS-MAP Localization Algorithm with Clustering and Fusion Compensation Strategy

WANG Jing, QIU Xiao-he   

  1. (College of Computer Science and Technology,Nanjing University of Technology,Nanjing 211816,China)
  • Received:2018-07-04 Online:2019-08-15 Published:2019-08-15

Abstract: The classic multi-dimensional scaling positioning (MDS-MAP)algorithm has the problem of high energy consumption and low positioning accuracy in large-scale wireless sensor networks.The improved MDS-MAP algorithm evaluates the residual energy,the balance of energy consumption and the local density of the cluster head when nodes are used as cluster heads and then the clustering is performed.The clusters have good connectivity and low energy loss.To overcome the limitation of the flattening rule,this paper proposed a method to obtain the unknown Euclidean distance between nodes,and the method of angle discrimination was used for eliminating the solution of interference.After compensating for common nodes,the improved rules was applied to the inter-cluster merging.Simulation and comparison results indicate that the proposed advanced MDS-MAP localization algorithm with clustering and fusion compensation strategy has lower splitting requirements,high positioning accuracy and robustness,which is good for the network expansion and the reduction of positioning power consumption

Key words: Clustering, MDS-MAP, Merging strategy, Wireless sensor network

CLC Number: 

  • TP393
[1]ZHANG D,LI G,ZHENG K,et al.An Energy Balanced Rou- ting Method Based on Forward Aware Factor for Wireless Sensor Network[J].IEEE Transactions on Industrial Informatics,2013,10(1):766-773.
[2]GHERBIC,ALIOUATZ,BENMOHAMMEDM.An Adaptive Clu- stering Approach to Dynamic Load Balancing and Energy Efficiency in Wireless Sensor Networks[J].Energy,2016,114(1):647-662.
[3]MU L,QU X M,ZHOU Z.SARL:A flexible simula-tion architecture of range-based location in WSN[C]∥The 35th Chinese Control Conference(CCC).Chengdu:IEEE,2016:8412-8417.
[4]GOLEIANM,POELLABAUERC.Localization in heterogeneous wireless sensor networks using elliptical range estimation[C]∥2016 International Conference on Computing,Networking and Communications.Kauai:IEEE 2016:1-7.
[5]CAPKUN S,HAMDI M,HUBAUX J P.GPS-Free Positioning in Mobile Ad-hoc Networks[J].Cluster Computing,2003,5(2):157-167.
[6]HIGHTOWER J,BORIELLO G,WANT R.SpotON:An Indoor 3D Location Sensing Technology Based on RF Signal Strength[R].Washington:University of Washington,2005.
[7]KARBASI A,OH S.Robust localization from incomplete local information[J].IEEE/ACM Transactions on Networking,2013,21(4):1131-1144.
[8]WANG X S,HU Y L.Research on Distribution Multidimensio- nal Scaling Localization Algorithm[J].Computer Science,2012,39(2):80-83,87.(in Chinese) 王新生,胡玉兰.分布式多维标度定位算法的研究[J].计算机科学,2012,39(2):80-83,87.
[9]FANG X M,JIANG Z H,NAN L,et al.Noise-aware localization algorithms for wireless sensor networks based on multidimensional scaling and adaptive Kalman filtering [J].Computer Communications,2017,101(1):57-68.
[10]PEI Z M.Wireless Sensor Network Localization Approach Based on Bayesian MDS[M].Germany:Springer Singapore,2018:709-716.
[11]TIAN H L,QIAN Z H,WANG Y J,et al.Modified MDS-MAP Localization Algorithm with Distance Error Correction in Energy Clustering Wireless Sensor Networks[J].Journal of Electronics and Information Technology,2017,39(7):1735-1740.(in Chinese) 田洪亮,钱志鸿,王义君,等.能量分簇传感器网络距离误差校正MDS-MAP定位算法[J].电子与信息学报,2017,39(7):1735-1740.
[12]ZHANG S,ER M J,ZHANG B H,et al.A Novel Heuristic Algorithm for Node Localization in Anisotropic Wireless Sensor Networks with Holes [J].Signal Processing,2017,138(1):27-34.
[13]JIA D,LIW H,WANG P,et al.An advanced distributed MDS-MAP localization algorithm with improved merging strategy[C]∥IEEE International Conference on Information and Automation.Macedonia:IEEE,2017:1980-1985.
[14]SHANG Y,RUML W.Improved MDS-based localization[C]∥Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies(IN-FOCOM 2004).Hong Kong:IEEE,2004:2640-2651.
[15]TANG L R,GONG Y,LUO Y T,et al.A 3D Position Algorithm Based on Euclidean for Wireless Sensor Networks[J].Acta Electronica Sinica,2012,40(4):821-825.(in Chinese) 唐良瑞,宫月,罗艺婷,等.一种基于Euclidean的无线传感器网络三维定位算法[J].电子学报,2012,40(4):821-825.
[16]GREGORY H,FEI S,NESTORC,et al.EE-LEACH:develop- ment of energy-efficient LEACH Protocol for data gathering in WSN[J].Eurasip Journal on Wireless Communications and Networking,2015,2015(1):1-9.
[17]JIN R,CHE Z,XU H,et al.An RSSI-based localization algo- rithm for outliers suppression in wireless sensor networks[J].Wireless Networks,2015,21(8):2561-2569.
[18]KANCHI S,WELCH C.An efficient algorithm for finding large localizable regions in wireless sensor networks[J].Procedia Computer Science,2013,19(2):1081-1087.
[19]BI Y,CHEN L N,MIAO C Y.Node Localization and Drifted Node Detection for WSN[J].Journal of Chinese Computer Systems,2018,39(1):189-192.(in Chinese) 毕烨,陈丽娜,苗春雨.无线传感器网络节点定位与漂移检测[J].小型微型计算机系统,2018,39(1):189-192.
[1] CHAI Hui-min, ZHANG Yong, FANG Min. Aerial Target Grouping Method Based on Feature Similarity Clustering [J]. Computer Science, 2022, 49(9): 70-75.
[2] LU Chen-yang, DENG Su, MA Wu-bin, WU Ya-hui, ZHOU Hao-hao. Federated Learning Based on Stratified Sampling Optimization for Heterogeneous Clients [J]. Computer Science, 2022, 49(9): 183-193.
[3] YU Shu-hao, ZHOU Hui, YE Chun-yang, WANG Tai-zheng. SDFA:Study on Ship Trajectory Clustering Method Based on Multi-feature Fusion [J]. Computer Science, 2022, 49(6A): 256-260.
[4] MAO Sen-lin, XIA Zhen, GENG Xin-yu, CHEN Jian-hui, JIANG Hong-xia. FCM Algorithm Based on Density Sensitive Distance and Fuzzy Partition [J]. Computer Science, 2022, 49(6A): 285-290.
[5] CHEN Jing-nian. Acceleration of SVM for Multi-class Classification [J]. Computer Science, 2022, 49(6A): 297-300.
[6] FAN Xing-ze, YU Mei. Coverage Optimization of WSN Based on Improved Grey Wolf Optimizer [J]. Computer Science, 2022, 49(6A): 628-631.
[7] CHEN Jia-zhou, ZHAO Yi-bo, XU Yang-hui, MA Ji, JIN Ling-feng, QIN Xu-jia. Small Object Detection in 3D Urban Scenes [J]. Computer Science, 2022, 49(6): 238-244.
[8] Ran WANG, Jiang-tian NIE, Yang ZHANG, Kun ZHU. Clustering-based Demand Response for Intelligent Energy Management in 6G-enabled Smart Grids [J]. Computer Science, 2022, 49(6): 44-54.
[9] XING Yun-bing, LONG Guang-yu, HU Chun-yu, HU Li-sha. Human Activity Recognition Method Based on Class Increment SVM [J]. Computer Science, 2022, 49(5): 78-83.
[10] ZHU Zhe-qing, GENG Hai-jun, QIAN Yu-hua. Line-Segment Clustering Algorithm for Chemical Structure [J]. Computer Science, 2022, 49(5): 113-119.
[11] ZHANG Yu-jiao, HUANG Rui, ZHANG Fu-quan, SUI Dong, ZHANG Hu. Study on Affinity Propagation Clustering Algorithm Based on Bacterial Flora Optimization [J]. Computer Science, 2022, 49(5): 165-169.
[12] ZUO Yuan-lin, GONG Yue-jiao, CHEN Wei-neng. Budget-aware Influence Maximization in Social Networks [J]. Computer Science, 2022, 49(4): 100-109.
[13] HAN Jie, CHEN Jun-fen, LI Yan, ZHAN Ze-cong. Self-supervised Deep Clustering Algorithm Based on Self-attention [J]. Computer Science, 2022, 49(3): 134-143.
[14] YANG Xu-hua, WANG Lei, YE Lei, ZHANG Duan, ZHOU Yan-bo, LONG Hai-xia. Complex Network Community Detection Algorithm Based on Node Similarity and Network Embedding [J]. Computer Science, 2022, 49(3): 121-128.
[15] PU Shi, ZHAO Wei-dong. Community Detection Algorithm for Dynamic Academic Network [J]. Computer Science, 2022, 49(1): 89-94.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!