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基于Bayes序贯估计的无线传感器网络数据融合算法

张书奎 崔志明 龚声蓉 孙涌 方巍

张书奎, 崔志明, 龚声蓉, 孙涌, 方巍. 基于Bayes序贯估计的无线传感器网络数据融合算法[J]. 电子与信息学报, 2009, 31(3): 716-721. doi: 10.3724/SP.J.1146.2008.00054
引用本文: 张书奎, 崔志明, 龚声蓉, 孙涌, 方巍. 基于Bayes序贯估计的无线传感器网络数据融合算法[J]. 电子与信息学报, 2009, 31(3): 716-721. doi: 10.3724/SP.J.1146.2008.00054
Zhang Shu-kui, Cui Zhi-ming, Gong Sheng-rong, Sun Yong, Fang Wei. A Data Fusion Algorithm Based on Bayes Sequential Estimation for Wireless Sensor Network[J]. Journal of Electronics & Information Technology, 2009, 31(3): 716-721. doi: 10.3724/SP.J.1146.2008.00054
Citation: Zhang Shu-kui, Cui Zhi-ming, Gong Sheng-rong, Sun Yong, Fang Wei. A Data Fusion Algorithm Based on Bayes Sequential Estimation for Wireless Sensor Network[J]. Journal of Electronics & Information Technology, 2009, 31(3): 716-721. doi: 10.3724/SP.J.1146.2008.00054

基于Bayes序贯估计的无线传感器网络数据融合算法

doi: 10.3724/SP.J.1146.2008.00054
基金项目: 

国家自然科学基金(60673092,60873116)和教育部科研重点项目(207040),江苏省自然科学基金(BK2008161),江苏省重大科技支撑与自主创新项目(BE200844)和苏州大学科研预研基金资助课题

A Data Fusion Algorithm Based on Bayes Sequential Estimation for Wireless Sensor Network

  • 摘要: 移动代理被认为是无线传感器网络中解决数据融合的有效方法,但代理访问节点的次序以及总数对算法有较大影响,为此该文提出一种基于Bayes序贯估计的移动代理数据融合算法.该算法通过构造特定数据结构的报文,在多跳环境中由Bayes序贯估计调整梯度向量,据此动态决定移动代理的访问路径,使移动代理有选择地在传感器节点之间移动,且在节点处由移动代理对数据进行融合,将多余的感知数据剔除,而不是把原始数据传输到Sink节点。理论分析和模拟实验表明,该算法有较小的能量消耗和传输延时。
  • Akyildiz I F and Weilian S, et al.. A survey on sensornetworks[J]. IEEE Communications Magazine, 2002, 40(12):102-114.[2]Qi H, Y Xu, and Wang X. Mobile-agent-based collaborativesignal and information processing in sensor networks[J].Proc.IEEE.2003, 91(8):1172-1183[3]Chang Jiun-jian, Hsiu Pi-cheng, and Kuo Tei-wei. Searchorienteddeployment strategies for wireless sensor networks[C]. 10th IEEE International Symposium on Object andComponent-Oriented Real-Time Distributed Computing(ISORC'07), Santorini Island, Greece, May 2007: 164-171.[4]Akkaya K and Younis M. A survey on routing protocols forwireless sensor networks[J].Ad hoc Networks.2005, 3(3):325-349[5]Joe I. A path selection algorithm with energy efficiency forwireless sensor networks[C]. 5th ACIS InternationalConference on Software Engineering Research, Management Applications (SERA 2007), Busan, South Korea, August2007: 419-423.[6]Chen M, Kwon T, and Choi Y. Data dissemination based onmobile agent in wireless sensor networks[C]. Proceedings ofthe IEEE Conference on Local Computer Networks 30thAnniversary (LCN05), Sydney, Australia, 2005: 1-2.[7]Lee Min-gu and Lee Sunggu. Data dissemination for wirelesssensor networks[C]. 10th IEEE International Symposium onObject and Component-Oriented Real-Time DistributedComputing (ISORC'07), Santorini Island, Greece, May 2007:172-180.[8]Wook C and Das S . A novel framework for energy-conservingdata gathering in wireless sensor networks[C]. Proceedings ofthe 24th Annual Joint Conference of the IEEE Computer andCommunications Societies (INFOCOM05), Miami, USA,2005: 1985-1996.[9]Wu Q, Rao N S V, and Barhen J, et al.. On computing mobileagent routes for data fusion in distributed sensor networks[J].IEEE Trans. on Knowledge and Data Engineering.2004,16(6):740-753[10]Hu Haifeng and Yang Zhen. Mobile-agent-based informationdrivenmultiresolution algorithm for target tracking inwireless sensor networks[C]. Qingdao, China, August 2007:521-525.[11]Shakshuki E, Xing Xinyu, and Malik H. Mobile agent forefficient routing among source nodes in wireless sensornetworks[C].Third International Conference on Autonomicand Autonomous Systems (ICAS'07), Athens, Greece, June2007: 39-44.
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出版历程
  • 收稿日期:  2008-01-11
  • 修回日期:  2008-09-29
  • 刊出日期:  2009-03-19

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