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Localization in sparse networks using sweeps
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Source International Conference on Mobile Computing and Networking archive
Proceedings of the 12th annual international conference on Mobile computing and networking table of contents
Los Angeles, CA, USA
SESSION: Sensor networks I table of contents
Pages: 110 - 121  
Year of Publication: 2006
ISBN:1-59593-286-0
Authors
David K. Goldenberg  Yale University
Pascal Bihler  Yale University
Ming Cao  Yale University
Jia Fang  Yale University
Brian D. O. Anderson  Australian National University
A. Stephen Morse  Yale University
Y. Richard Yang  Yale University
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Determining node positions is essential for many next-generation network functionalities. Previous localization algorithms lack correctness guarantees or require network density higher than required for unique localizability. In this paper, we describe a class of algorithms for fine-grained localization called Sweeps. Sweeps correctly finitely localizes all nodes in bilateration networks. Sweeps also handles angle measurements and noisy measurements. We demonstrate the practicality of our algorithm through extensive simulations on a large number of networks, upon which it consistently localizes one-thousand-node networks of average degree less than five in less than two minutes on a consumer PC.


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.

 
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Collaborative Colleagues:
David K. Goldenberg: colleagues
Pascal Bihler: colleagues
Ming Cao: colleagues
Jia Fang: colleagues
Brian D. O. Anderson: colleagues
A. Stephen Morse: colleagues
Y. Richard Yang: colleagues