无线传感器网络中继节点布居算法的研究

王翥; 王祁; 魏德宝; 王玲

doi:10.7498/aps.61.120505

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摘要

本文表述的是在该应用背景下引入多约束条件, 并采用枚举法与贪婪寻优算法相结合的方法, 解决了在可以作为中继节点设置位置的预设中继节点位置集合内, 合理选择中继节点设置位置以及既存网络因添加新传感器节点所引起的中继节点追加的问题. 仿真实验表明, 本文提出的中继节点布居与追加优化算法能够保证多约束条件下网络的容错性. 同时提出的基于最小网络距离因子评价标准, 有效提高了中继节点布居算法的能效性.

关键词:

作者及机构信息

1.
哈尔滨工业大学(威海)信息科学与工程学院, 威海 264209;

2.
哈尔滨工业大学电气工程及自动化学院, 哈尔滨 150001

基金项目: 国家自然科学基金(批准号: 60973162), 山东省自然科学基金(批准号: ZR2009GM037), 山东省科技攻关项目(批准号: 2010GGX10132)和山东省威海市高新技术开发区科技发展计划(批准号: 201025)资助的课题.

参考文献

[1]	Akyildiz I F, Su W. Sankarasubramaniam Y 2002 IEEE Communication Magazine 40 102
[2]	Wang Z, Wang Q, Hao X Q 2009 Proc. of WICOM'09, Beijing, China, 2009 p1
[3]	Yang Y, Blum R S, Sadler B M 2009 IEEE Transactions on Signal Processing 57 2050
[4]	Vaibhav P, Amarjeet K, Narottam C 2010 Journal of Electronic and Electrical Engineering 1 1
[5]	Zhang X, Ding X Y, LU S L 2009 Proceedings of the 5th WICOM, Beijing, China, 2009 p1
[6]	Xi Y F, Yeh E M 2008 IEEE Transactions on Information Theory 54 4081
[7]	Chang T Y, Hsu T C, Hong Y W 2010 IEEE Transactions on Signal Processing 58 1369
[8]	Nidito F, Battelli M, Basagni S 2007 Proceedings of IEEE 66th Vehicular Technology Conference 2007 p382
[9]	Xu H L, Huang L SH, Wang G 2009 Proceedings of 2009 Fifth International Conference on Mobile Ad-hoc and Sensor Networks, Fujian, China, 2009 p180
[10]	Cannons J, Milstein L B, Zeger K 2009 IEEE Transactions on Wireless Communications 8 5564
[11]	Li J S, Kao H C, Ke J D 2009 The Institution of Engineering and Technology 3 530
[12]	Cheng X, Du D, Wang L 2008 Wireless Networks 14 347
[13]	Pan J, Hou Y T, Cai, L, Shi Y 2003 Proc. of ACMMobicom'03, 2003 p 286
[14]	Bredin J L, Demaine E D, Hajiaghayi M T 2010 IEEE/ACM Transactions on Networking 18 216
[15]	He W L, Cao J 2010 IEEE Transactions on Neural Networks 21 571
[16]	Feng J W, Yam P, Austin F, Xu C 2011 Zeitschrift für Naturforschung A 66 6
[17]	Hao B, Tang J, Xue G L 2004 Proc. of HPSR'04, Phoenix 2004 p 246
[18]	Zhou J, Liu Y A, Wu F, Zhang H G, Zhu Y X 2011 Acta Phys. Sin. 60 090504 (in Chinese) [周杰, 刘元安, 吴帆, 张洪光, 俎云霄 2011 物理学报 60 090504]
[19]	Tang J, Hao B, Arunabha S 2006 Computer Communications 29 490
[20]	Cui S H, Chen G T, Qin S 2009 Journal of Hangzhou Dianzi University 29 107 (in Chinese) [崔素辉, 陈光亭, 辛双 2009 杭州电子科技大学学报 29 107]
[21]	Zhang W T, Yuan J, Yu Z, Xu Z X, Shan X M 2008 Acta Phys. Sin. 57 6896 (in Chinese) [张文铸, 袁坚, 俞哲, 徐赞新, 山秀明 2008 物理学报 57 6896]
[22]	Zhang W Y, Xue G L, Misra S 2007 Proc. of INFOCOM'07, Anchorage 2007 p1649
[23]	Misra S, Hong S D, Xue G L 2010 IEEE/ACM Transaction on Networking 18 434
[24]	Lin G H, Xue G L 1999 Information Processing Letters 69 53

施引文献

[1]	Akyildiz I F, Su W. Sankarasubramaniam Y 2002 IEEE Communication Magazine 40 102
[2]	Wang Z, Wang Q, Hao X Q 2009 Proc. of WICOM'09, Beijing, China, 2009 p1
[3]	Yang Y, Blum R S, Sadler B M 2009 IEEE Transactions on Signal Processing 57 2050
[4]	Vaibhav P, Amarjeet K, Narottam C 2010 Journal of Electronic and Electrical Engineering 1 1
[5]	Zhang X, Ding X Y, LU S L 2009 Proceedings of the 5th WICOM, Beijing, China, 2009 p1
[6]	Xi Y F, Yeh E M 2008 IEEE Transactions on Information Theory 54 4081
[7]	Chang T Y, Hsu T C, Hong Y W 2010 IEEE Transactions on Signal Processing 58 1369
[8]	Nidito F, Battelli M, Basagni S 2007 Proceedings of IEEE 66th Vehicular Technology Conference 2007 p382
[9]	Xu H L, Huang L SH, Wang G 2009 Proceedings of 2009 Fifth International Conference on Mobile Ad-hoc and Sensor Networks, Fujian, China, 2009 p180
[10]	Cannons J, Milstein L B, Zeger K 2009 IEEE Transactions on Wireless Communications 8 5564
[11]	Li J S, Kao H C, Ke J D 2009 The Institution of Engineering and Technology 3 530
[12]	Cheng X, Du D, Wang L 2008 Wireless Networks 14 347
[13]	Pan J, Hou Y T, Cai, L, Shi Y 2003 Proc. of ACMMobicom'03, 2003 p 286
[14]	Bredin J L, Demaine E D, Hajiaghayi M T 2010 IEEE/ACM Transactions on Networking 18 216
[15]	He W L, Cao J 2010 IEEE Transactions on Neural Networks 21 571
[16]	Feng J W, Yam P, Austin F, Xu C 2011 Zeitschrift für Naturforschung A 66 6
[17]	Hao B, Tang J, Xue G L 2004 Proc. of HPSR'04, Phoenix 2004 p 246
[18]	Zhou J, Liu Y A, Wu F, Zhang H G, Zhu Y X 2011 Acta Phys. Sin. 60 090504 (in Chinese) [周杰, 刘元安, 吴帆, 张洪光, 俎云霄 2011 物理学报 60 090504]
[19]	Tang J, Hao B, Arunabha S 2006 Computer Communications 29 490
[20]	Cui S H, Chen G T, Qin S 2009 Journal of Hangzhou Dianzi University 29 107 (in Chinese) [崔素辉, 陈光亭, 辛双 2009 杭州电子科技大学学报 29 107]
[21]	Zhang W T, Yuan J, Yu Z, Xu Z X, Shan X M 2008 Acta Phys. Sin. 57 6896 (in Chinese) [张文铸, 袁坚, 俞哲, 徐赞新, 山秀明 2008 物理学报 57 6896]
[22]	Zhang W Y, Xue G L, Misra S 2007 Proc. of INFOCOM'07, Anchorage 2007 p1649
[23]	Misra S, Hong S D, Xue G L 2010 IEEE/ACM Transaction on Networking 18 434
[24]	Lin G H, Xue G L 1999 Information Processing Letters 69 53

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无线传感器网络中继节点布居算法的研究

1. 哈尔滨工业大学(威海)信息科学与工程学院, 威海 264209;

2. 哈尔滨工业大学电气工程及自动化学院, 哈尔滨 150001

基金项目:

国家自然科学基金(批准号: 60973162), 山东省自然科学基金(批准号: ZR2009GM037), 山东省科技攻关项目(批准号: 2010GGX10132)和山东省威海市高新技术开发区科技发展计划(批准号: 201025)资助的课题.

收稿日期: 2011-07-28

修回日期: 2011-11-03

刊出日期: 2012-06-05

摘要: 本文表述的是在该应用背景下引入多约束条件, 并采用枚举法与贪婪寻优算法相结合的方法, 解决了在可以作为中继节点设置位置的预设中继节点位置集合内, 合理选择中继节点设置位置以及既存网络因添加新传感器节点所引起的中继节点追加的问题. 仿真实验表明, 本文提出的中继节点布居与追加优化算法能够保证多约束条件下网络的容错性. 同时提出的基于最小网络距离因子评价标准, 有效提高了中继节点布居算法的能效性.

关键词:

Relay node placement and addition algorithms in wireless sensor networks

1.
School of Information Science and Engineering, Harbin Institute of Technology at WeiHai, Weihai 264209, China;

2.
School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China

Fund Project:

Project supported by the National Natural Science Foundation of China (Grant No.60973162), the Natural Science Foundation of Shandong Province of China (Grant No. ZR2009GM037), the Science and technology of Shandong Province of China(Grant No.2010GGX10132), the Technology Research and Development Program of Weihai (Grant No. 2008011), and the Technology Research and Development Program of Weihai High-tech Development Zone in Shandong Province of China (Grant No. 201025)

Received Date: 28 July 2011

Accepted Date: 03 November 2011

Published Online: 05 June 2012

Abstract: The node placement is the foundation of network operation in wireless sensor networks. In many applications, the positions of gateway node and sensor node are relatively fixed. To guarantee network connectivity and reliability, some relay nodes must be reasonably placed between the gateway node and the sensor node. In the context of the above applications, we introduce many constraint conditions into the existing placement model, and adopt a hybrid placement method based on enumeration and greedy optimization algorithms to determine relay node positions from their candidate location sets, and we finally achieve the relay node initial placement and follow-up adjustment strategies, owing to new sensor nodes joining the current network. The simulation results demonstrate that our operable and optimized relay node placement algorithm can ensure multi-restricted fault-tolerant relay node placement, and the presented new evaluation standard based on the minimum distance factor can significantly improve the energy-efficiency of relay node placement algorithm.

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