self-configurable positioning technique for multi-hop wireless networks to appear in ieee...
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Self-Configurable Positioning Technique for Multi-hop Wireless Networks
To appear in IEEE Transaction on Networking
Chong Wang
Center of Advanced Computer Studies
University of Louisiana at Lafayette
Introduction Geographic location information
– Reduce routing overhead– Improve scalability– Intelligent coordination
Global vs. local positioning Our goal
– Self-configurability– Robustness– High accuracy
Related Work Global Positioning Techniques
– Global Positioning System (GPS[1])– Signpost Navigation System– Global Navigation Satellite System– Cellular Geolocation System– Drawbacks: hardware, signal obstruction
Local Positioning Techniques– GPS-free positioning [2] Not robust – Connectivity-based positioning [4] Inaccurate– GPS-less [3], Fine-grain [6], APS [5]
Convex[9], Recursive [10] Not self-configurable
Euclidean Distance Estimation
Crucial for positioning Proposed scheme
– Given node distribution
(a) (b)
Fig. 1. The Euclidean distance estimation model.
S
Z
D d
S D
Euclidean Distance Estimation (2) First hop
– within S’s range & closest to D– ’s coordinates
where
– 1-hop length Shortest path length
– Apply 1-hop estimation recursively
– Total path length
Coordinates Establishment Two steps: landmarks & regular nodes Landmarks– Estimate distance to each other – Exchange distance information– Define error function
– Minimize by using Simplex method
where
Coordinates Establishment (2)Coordinates Establishment (2) Regular nodes
– May be considered as landmarks, but not scalable
– Estimate dist. to landmarks– Define error function
– Minimize p
A B
CD
A B
CD
LAB
LCD
LBC
LADLAC
LBD
p
(a) (b)
Selection of Landmarks
Number of landmarks– The more landmarks, the
higher the accuracy.
Location of landmarks– Separated as far as possible
Algorithm of identifying corner nodes– Degree of center:
Cont’
Simulation And Discussion Simulation Model
– Simulator: Matlab– Variable parameters
– Number of nodes: 50 – 400– Number of landmarks: 3 – 8– Measurement inaccuracy: 0 – 40%
– Performance criteria– Coordinates error
– Computing time
Examples GPS tuning
N=50, no translation N=100, no translation N=400, no translation
N=50, center match N=100, center match N=400, center match
N=50, GPS tuning N=100, GPS tuning N=400, GPS tuning
with node density Impact of measurement error
Accuracy with more landmarks Delay with more landmarks
Simulation And DiscussionSimulation And Discussion
Conclusion We have proposed a self-configurable positioning technique for
multi-hop wireless networks. The proposed positioning technique is self-configurable and
independent of global position information. The coordinates error is determined by node density, one-hop
distance measurement inaccuracy, and the number of landmarks. The computing time for coordinates establishment is in the order
of milliseconds, which can be accepted by most applications in the mobile ad hoc networks as well as the sensor networks.
Reference: [1]B. Parkinson and S. Gilbert, “Navstar: global positioning system -- ten years later,” Proceedings of
the IEEE, pp. 1177--1186, 1983. [2]S. Capkun, M. Hamdi, and J.P. Hubaux, “Gps-free positioning in mobile ad-hoc networks,”
Proceedings of the 34th Annual Hawaii International Conference on System Sciences, 2001, pp. 3481--3490.
[3]D. Niculescu and B. Nath, “Ad hoc positioning system (APS),” Proceedings of IEEE Global Communications Conference GLOBECOM'01, 2001, pp. 2926--2931.
[4]Y. Shang, W. Ruml, and Y. Zhang, “Localization from mere connectivity, Proceedings of IEEE Mobile Ad Hoc Networking & Computing
(MobiHOC'03), 2003, pp. 201--212. [5]N. Bulusu, J. Heidemann, and D. Estrin, “GPS-less low cost outdoor localization for very small
devices,” IEEE Personal Communications Magazine, vol. 7, no. 5, pp. 28--34, 2000. [6]A. Savvides, C. Han, and M. B. Strivastava, “Dynamic fine-grained localization in ad-hoc networks
of sensors,” Proceedings of ACM/IEEE the 7th Annual International Conference on Mobile Computing and Networking (MobiCom'01), 2001, pp. 166--179. [7]T. Ng and H. Zhang, “Predicting the internet network distance with coordinates-based approaches,”
Proceedings of IEEE Conference on Computer Communication (INFOCOM '02), 2002, pp. 170--179. [8]J. Nelder and R. Mead, “A simplex method for function minimization,” Computer Journal, vol. 7,
pp. 308--313, 1965.