An efficient and self-adapting localization in static wireless sensor networks

Sensors

Volumn 9, Issue 8, 2009, Pages 6150-6170

  Teng, Guodong ^a,b   Zheng, Kougen ^a   Dong, Wei ^a  

^a ZHEJIANG UNIVERSITY   (China)

^b HANGZHOU NORMAL UNIVERSITY   (China)

Author keywords

Localization; Particle filter; Self Adapting Mobile Beacon assisted Localization (SA MBL); Wireless Sensor Networks (WSNs)

Indexed keywords

EXPERIMENTAL EVALUATION; FILTER-BASED; LOCALIZATION; PARTICLE FILTER; PROBABILISTIC METHODS; SELF ADAPTING; WIRELESS SENSOR NETWORK (WSNS);

DYNAMIC MODELS; MONTE CARLO METHODS; PROBABILITY DISTRIBUTIONS;

SENSOR NODES;

EID: 70349636343     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s90806150     Document Type: Article

References (24)

1. Akyildiz, I.F.; Su, W.; Sankarasubramaniam, Y.; Cayirci, E. A survey on sensor networks. IEEE Commun. Mag. 2002, 40, 102-114.
2. Hightower, J.; Borriello, G. Location systems for ubiquitous computing. IEEE Comput. 2001, 34, 57-66.
3. Teng, G.; Zheng, K.; Dong, W. Adapting mobile beacon-assisted localization in wireless sensor networks. Sensors 2009, 9, 2760-2779.
4. Priyantha, N.B.; Balakrishnan, H.; Demaine, E.D.; Teller, S. Mobile-assisted Localization in Wireless Sensor Networks. In Proceedings of The 24th Annual Joint Conference of the IEEE Computer and Communications Societies, Miami, FL, USA, 2005; pp. 172-183.
5. Kim, K.; Lee, W. MBAL: A Mobile Beacon-assisted Localization Scheme for Wireless Sensor Networks. In Proceedings of The 16th International Conference on Computer Communications and Networks, Honolulu, HI, USA, 2007; pp. 57-62.
6. Sichitiu, M.L.; Ramadurai, V. Localization of Wireless Sensor Networks with a Mobile Beacon. In Proceedings of The First IEEE Conference on Mobile Ad-hoc and Sensor Systems, Philadelphia, PA, USA, 2004; pp. 174-183.
7. Caballero, F.; Merino, L.; Maza, I.; Ollero, A. A Particle Filtering Method for Wireless Sensor Network Localization with an Aerial Robot Beacon. In Proceedings of IEEE International Conference on Robotics and Automation, Pasadena, CA, USA, 2008; pp. 596-601.
8. Marinakis, D.; Meger, D.; Rekleitis, I.; Dudek G. Hybrid Inference for Sensor Network Localization Using a Mobile Robot. In Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, Vancouver, BC, Canada, 2007; pp. 1089-1094.
9. Ihler, A.T.; Fisher, J.W.; Moses, R.L.; Willsky, A.S. Nonparametric belief propagation for self- localization of sensor networks. IEEE J. Sel. Area Comm. 2005, 23, 809-819.
10. Peng, R.; Sichitiu, M.L. Robust, Probabilistic, Constraint-Based Localization for Wireless Sensor Networks. In Proceedings of The Second Annual IEEE Sensor and Ad Hoc Communications and Networks, Santa Clara, CA, USA, 2005, pp. 541-550.
11. Li, M.; Liu, Y. Rendered Path: Range-Free Localization in Anisotropic Sensor Networks with Holes. In Proceedings of The 13th Annual ACM International Conference on Mobile Computing and Networking, Montreal, QU, Canada, 2007; pp. 51-62.
12. Stoleru, R.; He, T.; Stankovic, J.A. Walking gps: A Practical Solution for Localization in Manually Deployed Wireless Sensor Networks. In Proceedings of The 29th Annual IEEE International Conference on Local Computer Networks, Tampa, FL, USA, 2004; pp. 480-489.
13. Xiao, B.; Chen, H.K.; Zhou, S.G. A Walking Beacon-assisted Localization in Wireless Sensor Networks. In Proceedings of International Conference on Communications, Glasgow, Scotland, 2007; pp. 3070-3075.
14. Huang, R.; Zruba, G.V. Monte carlo localization of wireless sensor networks with a single mobile beacon. Wirel. Netw. 2008, doi: 10.1007/s11276-008-0096-3.
15. Teng, G.; Zheng, K.; Dong, W. MA-MCL: Mobile-Assisted Monte Carlo Localization for Wireless Sensor Networks. In Proceedings of The 4th Int'l Symp. on Innovations and Real-time Applications of Distributed Sensor Networks, Hangzhou, China, 2009; pp. 148-155.
16. Rudafshani, M.; Datta, S. Localization in Wireless Sensor Networks. In Proceedings of the 6th International Conference on Information Processing in Sensor Networks, Cambridge, MA, USA, 2007; pp. 51-60.
17. Woo, A.; Tong, T.; Culler, D. Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks. In Proceedings of the First International Conference on Embedded Networked Sensor Systems, Los Angeles, CA, USA, 2003; pp. 14-27.
18. Hu, L.; Evans, D. Localization for Mobile Sensor Networks. In Proceedings of the 10th Annual International Conference on Mobile Computing and Networking, New York, NY, USA, 2004; pp. 45-57.
19. Arulampalam, S.; Maskell, S.; Gordon, N. A tutorial on particle filters for online nonlinear/non- gaussian bayesian tracking. IEEE Trans. Signal Process. 2002, 50, 174-188.
20. Kitagawa, G. Monte carlo filter and smoother for non-gaussian nonlinear state space models. J. Comput. Graph. Stat. 1996, 5, 1-25.
21. Ross, S.M. Introduction to Probability Models, Ninth Edition; Academic Press: Burlington, MA, USA, 2006; pp. 663-680.
22. Nagpal, R.; Shrobe, H.; Bachrach, J. Organizing a Global Coordinate System from Local Information on an Ad Hoc Sensor Network. In Proceedings of Second International Workshop on Information Processing in Sensor Networks, Palo Alto, CA, USA, 2003; pp. 333-348.
23. Fox, D.; Burgard, W.; Dellaert, F. Monte Carlo Localization: Efficient Position Estimation for Mobile Robots. In Proceedings of The Sixteenth National Conference on Artificial Intelligence, Orlando, FL, USA, 1999; pp.343-349.
24. Fox, D. Adapting the sample size in particle filters through KLD-sampling. Int. J. Rob. Res. 2003, 22, 985-1003.