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Distributed computing paradigm for target classification in sensor networks
Zeng P(曾鹏); Huang Y(黄艳); Yu HB(于海斌)
Department工业控制系统研究室
Conference NameInternational Conference on Intelligent Computing (ICIC)
Conference DateAugust 16-19, 2006
Conference PlaceKunming, China
Author of SourceIEEE Computat Intelligence Soc, Int Neural Network Soc, Natl Sci Fdn China
Source PublicationCOMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS
PublisherSPRINGER-VERLAG
Publication PlaceBERLIN
2006
Pages1268-1278
Indexed BySCI ; EI ; CPCI(ISTP)
EI Accession number20064210172580
WOS IDWOS:000240083300159
Contribution Rank1
ISSN0302-9743
ISBN3-540-37274-1
AbstractIn this paper, we develop an energy and bandwidth efficient approach for target classification in sensor networks. Instead of adopting decision fusion to reduce network traffic as some recent research, we try to realize energy efficient target classification from a computational point of view. Our contribution is we propose a novel tree construction algorithm that autonomously organizes the distributed computation resources to execute the trained BP-network (BPN) in parallel manner. We evaluate the performance of our parallel computing paradigm compared to the traditional client/server-based computing paradigm from perspectives of energy consumption and communication traffic through analytical study. Finally, we take a target classification experiment to show the effectiveness of the proposed computing paradigm.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/8074
Collection工业信息学研究室_工业控制系统研究室
Corresponding AuthorZeng P(曾鹏)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Graduate School, Chinese Academy of Sciences, Beijing 100049, China
Recommended Citation
GB/T 7714
Zeng P,Huang Y,Yu HB. Distributed computing paradigm for target classification in sensor networks[C]//IEEE Computat Intelligence Soc, Int Neural Network Soc, Natl Sci Fdn China. BERLIN:SPRINGER-VERLAG,2006:1268-1278.
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