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WSN中一种能量有效的自适应协同节点选择方案

张余 蔡跃明 潘成康 徐友云

张余, 蔡跃明, 潘成康, 徐友云. WSN中一种能量有效的自适应协同节点选择方案[J]. 电子与信息学报, 2009, 31(9): 2193-2198. doi: 10.3724/SP.J.1146.2008.01441
引用本文: 张余, 蔡跃明, 潘成康, 徐友云. WSN中一种能量有效的自适应协同节点选择方案[J]. 电子与信息学报, 2009, 31(9): 2193-2198. doi: 10.3724/SP.J.1146.2008.01441
Zhang Yu, Cai Yue-ming, Pan Cheng-kang, Xu You-yun. An Energy-efficient Adaptive Cooperative Node Selection Scheme in WSN[J]. Journal of Electronics & Information Technology, 2009, 31(9): 2193-2198. doi: 10.3724/SP.J.1146.2008.01441
Citation: Zhang Yu, Cai Yue-ming, Pan Cheng-kang, Xu You-yun. An Energy-efficient Adaptive Cooperative Node Selection Scheme in WSN[J]. Journal of Electronics & Information Technology, 2009, 31(9): 2193-2198. doi: 10.3724/SP.J.1146.2008.01441

WSN中一种能量有效的自适应协同节点选择方案

doi: 10.3724/SP.J.1146.2008.01441
基金项目: 

江苏省自然科学基金(BK2007002), 国家自然科学基金(60672079)和东南大学移动通信国家重点实验室开放研究基金(N200814)资助课题

An Energy-efficient Adaptive Cooperative Node Selection Scheme in WSN

  • 摘要: 该文针对能量有限的无线传感器网络,提出了一种能量有效的自适应协同节点选择方案,该方案先根据预设的能量阈值来确定协同节点的可选集,再综合考虑可选节点的剩余能量和信道状况,选出最佳节点作为簇头节点的协同节点。通过对总能耗的最小化,获得不同传输距离对应的最优能量阈值;根据簇头节点与数据融合中心间的距离自适应地预设最优能量阈值,使总能耗最小。理论分析和仿真结果证明,该文方案能在传输能耗和电路能耗间找到最佳平衡点,有效地减小总能耗,使总能耗达到最小。
  • Akyildiz I F, Su W, and Sankarasubramaniam Y, et al.. Asurvey on sensor networks [J]. IEEE CommunicationsMagazine, 2002, 40(8): 102-114.[2]Cui S, Goldsmith A J, and Bahai A. Energy-efficiency ofMIMO and cooperative MIMO techniques in sensor networks[J].IEEE Journal Selected Areas Communication.2004, 22(6):1089-1098[3]Jayaweera S K. V-BLAST-based virtual MIMO fordistributed wireless sensor networks [J].IEEE Transactionson Communications.2007, 55(10):1867-1872[4]Jayaweera S K. Virtual MIMO-based cooperativecommunication for energy-constrained wireless sensornetworks [J].IEEE Transactions on Wireless Communication.2006, 5(5):984-989[5]Kim J and Lee W J. Cooperative relaying strategies formulti-hop wireless sensor networks [C]. COMSWARE 2008,Bangalore, 2008, 1: 103-106.[6]Simi?L, Berber S M, and Sowerby K W. Energy-efficiency ofcooperative diversity techniques in wireless sensornetworks[C]. PIMRC?7, Athens, 2007, 9: 1-5.[7]Nguyen T D, Berder O, and Sentieys O. Cooperative MIMOschemes optimal selection for wireless sensor networks[C].VTC2007-Spring, Dublin, 2007, 4: 85-89.[8]Ahmed I, Peng M, and Wang W. Uniform energyconsumption through adaptive rate communications incooperative MIMO based wireless sensor networks[C]. IEEEWiCom 2007. Shanghai, 2007, 10: 1-4.[9]Bravos G N, Efthymoglou G, and Kanatas A G. MIMO-basedand SISO Multihop Sensor Networks: Energy EfficiencyEvaluation[C]. WiMOB 2007, White Plains, NY, 2007, 10:13-20.[10]Himsoon T, Siriwongpairat W P, and Han Z, et al.. Lifetimemaximization by cooperative sensor and relay deployment inwireless sensor networks [C]. 2006 WCNC. Alaska, 2006, 4:439-444.[11]Lin Z, Erkip E, and Stefanov A. Cooperative regions andpartner choice in coded cooperative systems [J].IEEETransactions on Communications.2006, 54(7):1323-1334[12]Zhao B and Valenti M C. Practical relay networks: Ageneralization of hybrid-ARQ [J].IEEE Journal on SelectedAreas in Communications.2005, 23(1):7-18[13]Bletsas A, Khisti A, and Reed D P, et al.. A simplecooperative diversity method based on network path selection[J].IEEE Journal on Selected Areas in Communications.2006,24(3):659-672[14]Bravos G N and Kanatas A G. Energy efficiency ofMIMO-based sensor networks with a cooperative nodeselection algorithm [C]. ICC2007, Glasgow, 2007, 6:3218-3223.[15]Cui S, Goldsmith A J, and Bahai A. Energy-constrainedmodulation optimization [J] IEEE Transactions on WirelessCommunications, 2005, 4(5): 2349-2360.
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出版历程
  • 收稿日期:  2008-11-03
  • 修回日期:  2009-04-14
  • 刊出日期:  2009-09-19

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