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.