基于虚拟节点的无线传感器组网近似算法

doi:10.3969/j.issn.1000-3428.2013.12.019

计算机工程

基于虚拟节点的无线传感器组网近似算法

张洵彦，谢瑾奎，金一晟，杨宗源

(华东师范大学计算机科学与技术系，上海 200241)

收稿日期:2012-10-23 出版日期:2013-12-15 发布日期:2013-12-13
作者简介:张洵彦(1988－)，男，硕士研究生，主研方向：无线传感器网络，社会网络，算法博弈论；谢瑾奎(通讯作者)，讲师、博士；金一晟，硕士；杨宗源，教授、博士生导师
基金资助:
国家自然科学基金资助项目(61070226)

Wireless Sensor Networking Approximation Algorithm Based on Virtual Nodes

ZHANG Xun-yan, XIE Jin-kui, JIN Yi-sheng, YANG Zong-yuan

(Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China)

Received:2012-10-23 Online:2013-12-15 Published:2013-12-13

摘要/Abstract

摘要： 针对无线传感器网络中单纯路由控制或拓扑控制节能效用有限的问题，提出虚拟节点概念，并使用最小覆盖近似算法，给出虚拟节点在检测区域中的分布及基于虚拟节点的拓扑控制描述，在此基础上提出一种基于拓扑控制技术的组网近似算法。实验结果表明，该算法在节点数为1 500、覆盖半径分别为80、85、110时，完成传输数是单纯采用EOLSR算法的15.7倍、12.0倍和18.1倍，明显提高了节能效用。

关键词: 近似最小覆盖算法, 无线传感器网络, 拓扑控制, 节能组网, EOLSR路由算法, 组合技术

Abstract: Aiming at the problem of the energy-inefficiency of taking routing control or topology control only in Wireless Sensor Network(WSN). This paper considers a combination and presents a new concept: virtual node, gives the distribution of virtual wireless sensors in the detection area and a description of topology control based on virtual wireless sensor technology using the minimum cover approximation algorithm, and proposes a networking technology based on the above control technology. Experimental results show that, when node number is 1 500 and covering radius is 80, 85 and 110, the transmission number under the method is 15.7, 12.0, 18.1 times better than that under EOLSR, and the algorithm can significantly improve the energy-saving utility.

Key words: approximation minimal covering algorithm, Wireless Sensor Network(WSN), topology control, energy-efficient networking, EOLSR routing algorithm, combination technique

中图分类号:

TP391

张洵彦，谢瑾奎，金一晟，杨宗源. 基于虚拟节点的无线传感器组网近似算法[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2013.12.019.

ZHANG Xun-yan, XIE Jin-kui, JIN Yi-sheng, YANG Zong-yuan. Wireless Sensor Networking Approximation Algorithm Based on Virtual Nodes[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2013.12.019.

http://www.ecice06.com/CN/Y2013/V39/I12/87

参考文献

参考文献 [1] Giridhar A, Kumar P R. Maximizing the Functional Lifetime of Sensor Networks[C]//Proceedings of the 4th International Symposium on Information Processing in Sensor Networks. New York, USA: [s. n.], 2005: 5-12. [2] Dong Qunfeng. Maximizing System Lifetime in Wireless Sensor Networks[C]//Proceedings of the 4th International Symposium on Information Processing in Sensor Networks. New York, USA: [s. n.], 2005: 13-19. [3] Busse M, Haenselmann T, Effelsberg W. A Comparison of Lifetime-efficient Forwarding Strategies for Wireless Sensor Networks[C]//Proceedings of the 3rd International Workshop on Performance Evaluation of Wireless Ad Hoc, Sensor and Ubiquitous Networks. New York, USA: [s. n.], 2006: 33-40. (下转第96页) (上接第92页) [4] Liu Hai, Jia Xiaohua, Wan Pengjun. Maximizing Lifetime of Sensor Surveillance Systems[J]. IEEE/ACM Transactions on Networking, 2007, 15(2): 334-345. [5] Xue Yuan, Cui Yi, Nahrstedt K. Maximizing Lifetime for Data Aggregation in Wireless Sensor Networks[J]. Mobile Networks and Applications, 2005, 10(6): 853-864. [6] Pottie G, Kaiser W. Wireless Integrated Network Sensors[J]. Communications of the ACM, 2000, 43(5): 5l-58. [7] Howard A, Mataric M J, Sukhatme G S. Mobile Sensor Network Deployment Using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem[C]// Proceedings of the 6th International Symposium on Distributed Autonomous Robotic Systems. Fukuoka, Japan: [s. n.], 2002: 299-308. [8] Gupta H, Das S, Gu Q. Connected Sensor Cover: Self- organization of Sensor Networks for Efficient Query Execution[C]//Proceedings of ACM Mobile Ad Hoc Networking and Computing. New York, USA: [s. n.], 2003: 189-200. [9] Zhou Zongheng, Das S, Gupta H. Variable Radii Connected Sensor Cover in Sensor Networks[J]. IEEE Sensor and Ad Hoc Communications and Networks, 2004, 5(1): 387-396. [10] Cardei M. Improving Wireless Sensor Network Lifetime through Power Aware Organization[J]. ACM Wireless Networks, 2005, 11(3): 333-340. [11] 唐伟, 郭伟. 无线传感器网络中的最大生命期基因路由算法[J]. 软件学报, 2010, 21(7): 1646-1656. [12] Mahfoudh S, Minet P. Energy-aware Routing in Wireless ad Hoc and Sensor Networks[C]//Proceedings of the 6th International Wireless Communications and Mobile Computing Conference. Caen, France: [s. n.], 2010: 350-355. 编辑索书志

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