Dynamic cluster member selection method for multi-target tracking in wireless sensor network
Multi-target tracking (MTT) is a research hotspot of wireless sensor networks at present. A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member (CM) node selection method is put forward in the scheme. An...
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| Published in | Journal of Central South University Vol. 21; no. 2; pp. 636 - 645 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Heidelberg
Central South University
01.02.2014
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2095-2899 2227-5223 |
| DOI | 10.1007/s11771-014-1983-7 |
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| Abstract | Multi-target tracking (MTT) is a research hotspot of wireless sensor networks at present. A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member (CM) node selection method is put forward in the scheme. An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network. A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation. Then, the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection. This selection was fulfilled using genetic algorithm. Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state, and also indicate the validity of genetic algorithm in implementing CM node selection. |
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| AbstractList | Multi-target tracking (MTT) is a research hotspot of wireless sensor networks at present. A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member (CM) node selection method is put forward in the scheme. An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network. A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation. Then, the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection. This selection was fulfilled using genetic algorithm. Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state, and also indicate the validity of genetic algorithm in implementing CM node selection. |
| Author | Wen, Sha Liu, Li-jue Cai, Zi-xing |
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| CitedBy_id | crossref_primary_10_1016_j_future_2017_12_011 crossref_primary_10_1016_j_adhoc_2018_03_009 crossref_primary_10_1177_1550147717703115 crossref_primary_10_1007_s11771_016_3110_4 crossref_primary_10_46532_jce_20200702 crossref_primary_10_3390_s22155675 |
| Cites_doi | 10.1109/TCE.2010.5681097 10.1360/crad20050121 10.1109/TPDS.2002.1036066 10.1109/TC.2007.70792 10.1002/ett.1466 10.1109/TNET.2009.2022936 10.1007/s11704-011-0361-y 10.1007/s11768-011-0249-2 10.1109/TIM.2008.2005822 10.1109/ICMLC.2009.5212296 10.1109/MAHSS.2008.4660057 10.1145/938985.938995 |
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| Keywords | wireless sensor networks collaborative task allocation dynamic cluster multi-target tracking comprehensive performance index function |
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