Implementation of the CCA-MAP localization algorithm on a wireless sensor network testbed

Wireless sensor networks (WSNs) are usually randomly deployed in a region of interest. As a result, algorithms that can compute the location of sensor nodes within a WSN are needed. In recent years, several localization algorithms have been proposed for stationary WSNs. However, most studies only provide simulation results and most algorithms have never been implemented on a real testbed. In this paper, we implement a localization algorithm called CCA-MAP on a real WSN testbed. To the best of our knowledge, the CCA-MAP algorithm is amongst the best performing algorithms proposed for stationary WSNs. The results obtained show that the implementation results are consistent with the simulation results.

[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]  Radu Stoleru,et al.  Mobile Sensor Network Localization in Harsh Environments , 2010, DCOSS.

[3]  Mihail L. Sichitiu,et al.  Localization of wireless sensor networks with a mobile beacon , 2004, 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975).

[4]  Li Li,et al.  Localization applying an efficient neural network mapping , 2007, Autonomics.

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

[6]  Fengqi Yu,et al.  A Localization Algorithm for Mobile Wireless Sensor Networks , 2007 .

[7]  Ying Zhang,et al.  Localization from connectivity in sensor networks , 2004, IEEE Transactions on Parallel and Distributed Systems.

[8]  Azzedine Boukerche,et al.  A novel lightweight algorithm for time-space localization in wireless sensor networks , 2007, MSWiM '07.

[9]  Wheeler Ruml,et al.  Improved MDS-based localization , 2004, IEEE INFOCOM 2004.

[10]  Erik D. Demaine,et al.  Anchor-Free Distributed Localization in Sensor Networks , 2003 .

[11]  Ying Zhang,et al.  Localization from mere connectivity , 2003, MobiHoc '03.

[12]  Andrea Zanella,et al.  Testbed implementation and refinement of a range-based localization algorithm for wireless sensor networks , 2006, Mobility '06.

[13]  Tarek F. Abdelzaher,et al.  Range-free localization schemes for large scale sensor networks , 2003, MobiCom '03.

[14]  John W. Fisher,et al.  Nonparametric belief propagation for self-localization of sensor networks , 2005, IEEE Journal on Selected Areas in Communications.

[15]  Wanming Chen,et al.  A Localization Algorithm Based on Discrete Imprecision Range Measurement in Wireless Sensor Networks , 2006, 2006 IEEE International Conference on Information Acquisition.

[16]  Weiming Shen,et al.  A testbed for localization and tracking in wireless sensor networks , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[17]  Deborah Estrin,et al.  GPS-less low-cost outdoor localization for very small devices , 2000, IEEE Wirel. Commun..

[18]  Andrea Zanella,et al.  Experimental comparison of RSSI-based localization algorithms for indoor wireless sensor networks , 2008, REALWSN '08.

[19]  C. Alippi,et al.  Wireless sensor networks and radio localization: a metrological analysis of the MICA2 received signal strength indicator , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

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

[21]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[22]  Li Li,et al.  Cooperative node localization using nonlinear data projection , 2009, TOSN.

[23]  Jeanny Hérault,et al.  Curvilinear component analysis: a self-organizing neural network for nonlinear mapping of data sets , 1997, IEEE Trans. Neural Networks.