ACM Home Page
Please provide us with feedback. Feedback
Localization from mere connectivity
Full text PdfPdf (659 KB)
Source International Symposium on Mobile Ad Hoc Networking & Computing archive
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing table of contents
Annapolis, Maryland, USA
SESSION: Sensor networks table of contents
Pages: 201 - 212  
Year of Publication: 2003
ISBN:1-58113-684-6
Authors
Yi Shang  University of Missouri, Columbia, MO
Wheeler Ruml  Palo Alto Research Center, Palo Alto, CA
Ying Zhang  Palo Alto Research Center, Palo Alto, CA
Markus P. J. Fromherz  Palo Alto Research Center, Palo Alto, CA
Sponsors
ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 25,   Downloads (12 Months): 233,   Citation Count: 82
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/778415.778439
What is a DOI?

ABSTRACT

It is often useful to know the geographic positions of nodes in a communications network, but adding GPS receivers or other sophisticated sensors to every node can be expensive. We present an algorithm that uses connectivity information who is within communications range of whom to derive the locations of the nodes in the network. The method can take advantage of additional information, such as estimated distances between neighbors or known positions for certain anchor nodes, if it is available. The algorithm is based on multidimensional scaling, a data analysis technique that takes O(n3) time for a network of n nodes. Through simulation studies, we demonstrate that the algorithm is more robust to measurement error than previous proposals, especially when nodes are positioned relatively uniformly throughout the plane. Furthermore, it can achieve comparable results using many fewer anchor nodes than previous methods, and even yields relative coordinates when no anchor nodes are available.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
I. Borg and P. Groenen. Modern Multidimensional Scaling, Theory and Applications. Springer-Verlag, New York, 1997.
 
2
A. Buja, D. F. Swayne, M. Littman, N. Dean, and H. Hofmann. XGvis: Interactive data visualization with multidimensional scaling. Journal of Computational and Graphical Statistics, page (to appear), 2001.
 
3
N. Bulusu, J. Heidemann, and D. Estrin. GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications, 7(5):28--34, Oct. 2000.
 
4
L. Doherty, L. E. Ghaoui, and K. Pister. Convex position estimation in wireless sensor networks. In Proc. Infocom 2001, Anchorage, AK, April 2001.
 
5
D. Ganesan, B. Krishnamachari, A. Woo, D. Culler, D. Estrin, and S. Wicker. An empirical study of epidemic algorithms in large scale multihop wireless networks. Technical report UCLA/CSD-TR-02-0013, UCLA Computer Science Department, 2002.
 
6
 
7
A. Howard, M. J. Mataric, and G. S. Sukhatme. Relaxation on a mesh: a formalism for generalized localization. In Proc. IEEE/RSJ Int'l Conf. on Intelligent Robots and Systems (IROS01), pages 1055--1060, 2001.
8
 
9
D. Niculescu and B. Nath. Ad-hoc positioning system. In IEEE GlobeCom, Nov. 2001.
 
10
S. I. Roumeliotis and G. A. Bekey. Synergetic localization for groups of mobile robots. In Proc. 39th IEEE Conf. on Decision and Control, Sydney, Australia, Dec. 2000.
 
11
12
13
 
14
R. N. Shepard. Analysis of proximities: Multidimensional scaling with an unknown distance function I & II. Psychometrika, 27:125--140, 219--246, 1962.
 
15
W. S. Torgeson. Multidimensional scaling of similarity. Psychometrika, 30:379--393, 1965.

CITED BY  82

Collaborative Colleagues:
Yi Shang: colleagues
Wheeler Ruml: colleagues
Ying Zhang: colleagues
Markus P. J. Fromherz: colleagues