大规模传感器网络局部半定规划的节点定位算法

周旭 1; 李善仓 2; 3; 王新珩 2

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大规模传感器网络局部半定规划的节点定位算法

更新时间：2025-07-09

- 大规模传感器网络局部半定规划的节点定位算法
- Nodes Locating Algorithm Based on Local Semi-Definite Programming for Large Scale Wireless Sensor Networks
- 西安交通大学学报 2009年43卷第8期页码：38-42
- 作者机构：
  
  西安电子科技大学雷达信号处理国家重点实验室,西安,710072
- 作者简介：
- 基金信息：
  
  : 2008-10-24. 作者简介: 周旭(1963-),男,博士生;王新珩(联系人),教授. 基金项目: 国家高技术研究发展计划资助项目(2005AA121130)
- DOI：
  中图分类号： TP393
- 网络首发：2009-08-10，
  
  纸质出版：2009
- 稿件说明：
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周旭 1, 李善仓 2, 3, 等. 大规模传感器网络局部半定规划的节点定位算法[J]. 西安交通大学学报, 2009,43(8):38-42.

Nodes Locating Algorithm Based on Local Semi-Definite Programming for Large Scale Wireless Sensor Networks[J]. 2009, 43(8): 38-42.
周旭 1, 李善仓 2, 3, 等. 大规模传感器网络局部半定规划的节点定位算法[J]. 西安交通大学学报, 2009,43(8):38-42. DOI：

Nodes Locating Algorithm Based on Local Semi-Definite Programming for Large Scale Wireless Sensor Networks[J]. 2009, 43(8): 38-42. DOI：

摘要

针对大规模无线传感器网络中节点定位问题

提出了一种高效、准确、分布式的局部半定规划(LSDP)定位算法.根据节点重要度

将大规模无线传感器网络分割为多个局部网络

局部网络采用半定规划的方法对其辖内的节点进行相对定位构建的局部相对映射

应用合并算法将局部相对映射拼接为全局相对映射

再通过参考节点匹配将全局相对映射转换为全局绝对映射

从而获得整个无线传感器网络内部所有节点的详细位置信息.实验结果表明

网络在规则分布下

LSDP的节点定位误差仅为理想通信时的98%

在随机均匀分布下的定位误差减小了90%.

Abstract

Aiming at the locating problem in large scale wireless sensor networks

a local SDP algorithm(LSDP)is proposed. A large scale wireless sensor network is split into some local networks according to a node importance index of each node

and a relative map in each local network is then obtained with SDP. All relative maps are patched into a global relative map. After matching with reference nodes

the global relative map is transformed into a global absolute map

and then all nodes in the network are located. Simulation results show that the location error is as little as 98% of that in ideal communications when WSN is regularly deployed. The location error is reduced by 90% if WSN is randomly deployed.

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references

AHMED A A, HONGCHI S. Network-aware positioning in sensor networks [C]∥IEEE International Conference on Mobile Ad hoc and Sensor Systems. Piscataway, NJ, USA: IEEE, 2005: 8-10.

BISWAS P, LIAN T C, WANG C, et al. Semidefinite programming based algorithms for sensor network localization [J]. ACM Trans on Sensor Networks, 2006, 2(2): 188-220.

BISWAS P, YE Y. Semidefinite programming for ad hoc wireless sensor network localization [C]∥Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks. New York, USA: ACM, 2004:46-54.

BISWAS P, LIANG T C, TOH K C, et al. Semidefinite programming approaches for sensor network localization with noisy distance measurements [J]. IEEE Trans on Automation Science and Engineering, 2006, 3(4): 360-371.

DIMOKAS N, KATSAROS D. Node clustering in wireless sensor networks by considering structural characteristics of the network graph [C]∥Proceedings of 4th International Conference on Information Technology. Los Alamitos, CA, USA: IEEE Computer Society, 2007:122-127.

LI Shancang, ZHANG Deyun. A novel manifold learning algorithm for localization estimation in wireless sensor networks [J]. IEICE Trans on Communication, 2007, 90-B(12): 3496-3500.

LI Shancang, WANG Xinheng, ZHANG Deyun. Source nodes localization algorithm for large scale wireless sensor networks using self-organizing isometric mapping [J]. International Journal of Sensor Networks, 2009,5(4):11-19.

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