Accurate and Lightweight Range-Free Localization for Wireless Sensor Networks

Wireless sensor networks demands proper means in order to obtain an accurate location of their nodes for a twofold reason: on the one hand, the exchanged data must be spatially meaningful since their content may be unusual if the location of where they have been produced is not associated to them, on the other hand, such networks need efficient routing algorithms where optimal routing decisions must be based on location information. Accuracy is not the only demands for positioning of sensors, but also simplicity and infrastructure independence in order to avoid excessive energy consumption and deployment costs. For these reasons, GPS is not used but the RF technologies are mainly preferred. Based on those technologies, most of the solutions tailored for sensors are designed so as to determine a location based on simple measurements of the signal intensity of the received messages. Despite being able to satisfy the peculiar requirements for localization in sensor networks, those methods have been proved to be particularly inaccurate, due to the unreliability of the adopted measurements upon which location is inferred. This article proposes a novel approach for range-free localization by obtaining intensity measurements at different Power of Transmission levels, using them as inputs for multiple location estimators, and aggregating the outputs of those estimators in order to achieve a more accurate determination of a sensor position. We have implemented our solution on real sensor platforms and performed some experiments in order to show how this simple solution allows halving the localization error and reducing the energy consumption of about 18% with respect to the state-of-the-art algorithms.

[1]  Rami G. Melhem,et al.  A unified interference/collision model for optimal MAC transmission power in ad hoc networks , 2006, Int. J. Wirel. Mob. Comput..

[2]  Xiaoli Li,et al.  Cramer-Rao Bound Analysis of Quantized RSSI Based Localization in Wireless Sensor Networks , 2005, 11th International Conference on Parallel and Distributed Systems (ICPADS'05).

[3]  Matt Welsh,et al.  Simulating the power consumption of large-scale sensor network applications , 2004, SenSys '04.

[4]  Christian Esposito,et al.  Deployment of RSS-Based Indoor Positioning Systems , 2011, Int. J. Wirel. Inf. Networks.

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

[6]  Ignas Niemegeers,et al.  A survey of indoor positioning systems for wireless personal networks , 2009, IEEE Communications Surveys & Tutorials.

[7]  Domenico Cotroneo,et al.  Automated Generation of Performance and Dependability Models for the Assessment of Wireless Sensor Networks , 2012, IEEE Transactions on Computers.

[8]  Kui Wu,et al.  Sensor localization with Ring Overlapping based on Comparison of Received Signal Strength Indicator , 2004, 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975).

[9]  R.L. Moses,et al.  Locating the nodes: cooperative localization in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[10]  Qinye Yin,et al.  Distributed Angle Estimation for Localization in Wireless Sensor Networks , 2013, IEEE Transactions on Wireless Communications.

[11]  JAMAL N. AL-KARAKI,et al.  Routing techniques in wireless sensor networks: a survey , 2004, IEEE Wireless Communications.

[12]  Philip Levis,et al.  The nesC language: a holistic approach to networked embedded systems , 2003, SIGP.

[13]  Marcello Cinque,et al.  Leveraging Power of Transmission for Range-Free Localization of Tiny Sensors , 2012, W2GIS.

[14]  David E. Culler,et al.  Versatile low power media access for wireless sensor networks , 2004, SenSys '04.

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

[16]  Stefano Russo,et al.  ROCRSSI++: An Efficient Localization Algorithm for Wireless Sensor Networks , 2011, Int. J. Adapt. Resilient Auton. Syst..