Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/15253
Title: Robust localization against outliers in wireless sensor networks
Authors: Xiao, Q
Bu, K
Wang, Z
Xiao, B 
Issue Date: 2013
Publisher: Association for Computing Machinary
Source: ACM transactions on sensor networks, 2013, v. 9, no. 2, 24 How to cite?
Journal: ACM transactions on sensor networks 
Abstract: In wireless sensor networks, a critical system service is the localization service that determines the locations of geographically distributed sensor nodes. The raw data used by this service are the distance measurements between neighboring nodes and the position knowledge of anchor nodes. However, these rawdata may contain outliers that strongly deviate from their true values, which include both the outlier distances and the outlier anchors. These outliers can severely degrade the accuracy of the localization service. Therefore, we need a robust localization algorithm that can reject these outliers. Previous studies in this field mainly focus on enhancing multilateration with outlier rejection ability, since multilateration is a primitive operation used by localization service. But patch merging, a powerful operation for increasing the percentage of localizable nodes in sparse networks, is almost neglected. We thus propose a robust patch merging operation that can reject outliers for both multilateration and patch merging. Based on this operation, we further propose a robust network localization algorithm called RobustLoc. This algorithm makes two major contributions. (1) RobustLoc can achieve a high percentage of localizable nodes in both dense and sparse networks. In contrast, previous methods based on robust multilateration almost always fail in sparse networks with average degrees between 5 and 7. Our experiments show that RobustLoc can localize about 90% of nodes in a sparse network with 5.5 degrees. (2) As far as we know, RobustLoc is the first to uncover the differences between outlier distances and outlier anchors. Our simulations show that RobustLoc can reject colluding outlier anchors reliably in both convex and concave networks.
URI: http://hdl.handle.net/10397/15253
ISSN: 1550-4859
EISSN: 1550-4867
DOI: 10.1145/2422966.2422981
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

12
Last Week
0
Last month
1
Citations as of Jul 21, 2017

WEB OF SCIENCETM
Citations

6
Last Week
0
Last month
0
Citations as of Aug 13, 2017

Page view(s)

32
Last Week
1
Last month
Checked on Aug 14, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.