异构传感器网络中汇聚节点位置优化路由算法

doi:10.3969/j.issn.1000-436x.2013.z1.036

通信学报 ›› 2013, Vol. 34 ›› Issue (Z1): 268-275.doi: 10.3969/j.issn.1000-436x.2013.z1.036

异构传感器网络中汇聚节点位置优化路由算法

邹赛^1,²,汪文勇¹,唐勇¹,张骏¹

¹ 电子科技大学计算机科学与工程学院，四川成都 611731
² 重庆电子工程职业学院软件学院，重庆 401331

出版日期:2013-08-25 发布日期:2017-06-23
基金资助:
重庆市2013年教育科学规划基金资助项目;湖南省科技厅计划基金资助项目

Routing algorithm based on location optimization of sink node in hybrid wireless sensor networks

Sai ZOU^1,²,Wen-yong WANG¹,Yong TANG¹,Jun ZHANG¹

¹ School of Computer Science and Engineering ,University of Electronic Science and Technology , Chengdu 611731, China
² School of Software Engineering , Chongqing College of Electronic Engineering, Chongqing 401331,China

Online:2013-08-25 Published:2017-06-23
Supported by:
Project by Chongqing education science In 2013;Project supported by Hunan Provincial Science and Technol-ogy Program of China

摘要/Abstract

摘要：

在异构无线传感器网络模型下，针对采集节点发送数据能量消耗过高及路由时分组丢失率过大等情况，对数据汇聚节点的位置优化及路由进行了研究，提出了移动汇聚节点位置优化路由算法（MLOYIH）。先根据蚁群算法的原理对移动节点与静态节点进行分组，再在组内寻找适合的位置放置汇聚节点，最后根据供电情况，选择合适的跳算进行路由。经过仿真实验与性能分析表明，MLOYIH算法与传统算法比较，能量消耗降低到64%，分组丢失率不高于3%。

关键词: 异构传感器网络, 移动节点, 位置优化, 路由

Abstract:

The data acquisition nodes in hybrid wireless sensor network usually suffer high energy consumption of data transmission and high ratio of packet loss. This issue is closely related to the position of data aggregation nodes (sink nodes) and can be improved by optimizing the location of these nodes. It was adopted in the routing algorithm based on location optimization of mobile sink nodes (MLOYIH). In MLOYIH, ant colony algorithm was used to divide the mobile nodes and static nodes into groups and then the suitable positions of the aggregation nodes were determined within each group. Then the suitable networking routing was established according to the power supply of sensor nodes. Simulation shows that MLOYIH algorithm has a lower energy consumption with a reduction of 64% compared with the traditional algorithms, and the ratio of packet loss is less than 3%.

Key words: hybrid wireless sensor networks, mobile node, optimal location, routing

邹赛,汪文勇,唐勇,张骏. 异构传感器网络中汇聚节点位置优化路由算法[J]. 通信学报, 2013, 34(Z1): 268-275.

Sai ZOU,Wen-yong WANG,Yong TANG,Jun ZHANG. Routing algorithm based on location optimization of sink node in hybrid wireless sensor networks[J]. Journal on Communications, 2013, 34(Z1): 268-275.

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参考文献 15

[1]	ZOU Q M , QIN L J , MA Q Y . The application of the internet of things in the smart grid[J]. Materials Science and Information Technology, 2012,433(440):3388-3394.
[2]	BEZDEK J C , RAJASEGARAR S , LECKIE C , et al. Anomaly detec-tion in environmental monitoring networks[J]. IEEE Computational Intelligence Magazine, 2011,5(6):52-58.
[3]	TOPCUOGLU H , ERMIS M , BEKMEZCI I . A new three- dimen-sional wireless multimedia sensor network simulation environment for connected coverage problems[J]. Simulation-transactions of the Soci-ety for Modeling and Simulation International, 2012,88(1):110-122.
[4]	CHEN F , DELANNAY D , VLEESCHOUWER C D . An autonomous framework to produce and distribute personalized team-sport video summaries: a basketball case study[J]. IEEE Transactions on Multi-media, 2011,13(6):1381-1394.
[5]	HUNG C C , PENG W C , LEE W C . Energy-aware set-covering ap-proaches for approximate data collection in wireless sensor net-works[J]. IEEE Transactions on Knowledge and Data Engineering, 2012,24(11):1993-2007.
[6]	DENG X , YANG Y Y . Online adaptive compression in delay sensi-tive wireless sensor networks[J]. IEEE Transactions on Computers, 2012,61(10):1429-1442.
[7]	PAOLO M , JEREMIE L , GIANLUIGI F . Energy-efficient mobile target detection in wireless sensor networks with random node de-ployment and partial coverage[J]. Pervasive and Mobile Computing, 2012,8(3):429-447.
[8]	HABIBM A . On the problem of k-coverage in mission-oriented mo-bile wireless sensor networks[J]. Computer Networks, 2012,56(7):1935-1950.
[9]	NACHIKET V K , SRINIVASA M . Maximum entropy principle-based algorithm for simultaneous resource location and multihop routing in multiagent networks[J]. IEEE Transactions on Mobile Computing, 2012,11(4):591-602.
[10]	YU S W . Energy optimal control in mobile sensor networks using hybrid systems theory[A]. 2011 IEEE International Conference[C]. Anchorage, Alaska, USA, 2011.1975-1980.
[11]	ABABNAH A . Optimal control-based strategy for sensor deploy-ment[J]. IEEE Transactions on Systems and Humans, 2011,41:97-104.
[12]	DENG J P , WANG M Q , SONG X H . CdS and CdSe quantum dots subsectionally sensitized solar cells using a novel double-layer ZnO nanorod arrays[J]. Journal of colloid and interface science, 2012,388(1):18-22.
[13]	苏玉娥．无线传感器网络中移动Agent路由算法的研究[D]．徐州：中国矿业大学， 2010. SU Y E , . Research on Mobile Agent Routing Algorithm in Wireless Sensor Networks[D]. XuZhou: China University of Mining and Tech-nology, 2010.
[14]	路秀英，崔兴凯，霍新丽．求解多目标资源分配问题的改进蚁群优化算法[J]．微电子学与计算机， 2011,28(10):87-90. LU X Y , CUI X K , HUO X L . Improved ant colony optimization to multi-objective resource allocation problems[J]. Microelectronics ＆Comput, 2011,28(10):87-90.
[15]	梁兵．广义费尔马点的几何解法[J]．山东师范大学学报（自然科学版）， 2011,1(26):133-134. LIANG B . Geometric solution of generalized Fermat point[J]. Journal of Shandong Normal University (Natural Science), 2011,1(26):133-134.

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异构传感器网络中汇聚节点位置优化路由算法

Routing algorithm based on location optimization of sink node in hybrid wireless sensor networks

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