Experimental Analysis of Area Localization Scheme for Sensor Networks

For large wireless sensor networks, identifying the exact location of every sensor may not be feasible or necessary. A coarse estimate of the sensors' locations is usually sufficient for many applications. An efficient area localization scheme (ALS) has been proposed for large sensor networks. ALS is a range-free localization scheme that tries to estimate the position of a sensor within a certain area rather than its exact location. As the complex calculations are handled by the powerful sinks instead of the sensors, this reduces the energy consumed by the sensors and helps to extend the lifetime of the network. In this paper, we discuss the implementation of ALS using MICAz motes and the localization experiments carried out in both indoor and outdoor environments. We also propose algorithms and techniques to improve the accuracy of ALS in realistic deployment scenarios. We observed that the performance of ALS is comparable or better than other localization schemes that have been implemented while ALS has lower complexity and hardware requirements.

[1]  L. El Ghaoui,et al.  Convex position estimation in wireless sensor networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[2]  Andreas F. Molisch,et al.  Localization via Ultra- Wideband Radios , 2005 .

[3]  John A. Stankovic,et al.  Probability grid: a location estimation scheme for wireless sensor networks , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[4]  G.B. Giannakis,et al.  Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks , 2005, IEEE Signal Processing Magazine.

[5]  Yu Ge,et al.  An area localization scheme for large wireless sensor networks , 2005, 2005 IEEE 61st Vehicular Technology Conference.

[6]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[7]  Bhaskar Krishnamachari,et al.  Ecolocation: a sequence based technique for RF localization in wireless sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[8]  Winston Khoon Guan Seah,et al.  Density-aware hop-count localization (DHL) in wireless sensor networks with variable density , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[9]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .

[10]  Andreas Savvides,et al.  An Empirical Characterization of Radio Signal Strength Variability in 3-D IEEE 802.15.4 Networks Using Monopole Antennas , 2006, EWSN.

[11]  Srdjan Capkun,et al.  GPS-free Positioning in Mobile Ad Hoc Networks , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[12]  Matt Welsh,et al.  MoteTrack: a robust, decentralized approach to RF-based location tracking , 2005, Personal and Ubiquitous Computing.

[13]  B. R. Badrinath,et al.  DV Based Positioning in Ad Hoc Networks , 2003, Telecommun. Syst..