Effective neural network-based node localisation scheme for wireless sensor networks

IET Wireless Sensor Systems

Volumn 4, Issue 2, 2014, Pages 97-103

  Chuang, Po Jen ^a   Jiang, Yi Jun ^a  

^a TAMKANG UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COST BENEFIT ANALYSIS; TOPOLOGY;

ADDITIONAL COSTS; DISTANCE ESTIMATION; EXPERIMENTAL EVALUATION; NETWORK MODELING; NETWORK-BASED; NODE LOCALISATION; ONLINE TRAINING; RECEIVED SIGNAL STRENGTH INDICATION;

SENSOR NODES;

EID: 84901931524     PISSN: 20436386     EISSN: 20436394     Source Type: Journal    
DOI: 10.1049/iet-wss.2013.0055     Document Type: Article

References (20)

1. Dana, A., Zadeh, A.K., Hekmat, B.: 'Localization in ad-hoc networks'. Proc. IEEE Int. Conf. Telecommunications and Int. Conf. Communications, Malaysia, May 2007, pp. 313-317
2. Liu, R., Sun, K., Shen, J.: 'BP localization algorithm based on virtual nodes in wireless sensor networks'. Proc. Sixth Int. Conf. Wireless Communications, Networking and Mobile Computing, 2010, Article No. 5601391
3. Chuang, P.-J., Wu, C.-P.: 'An effective PSO-based node localization scheme for wireless sensor networks'. Proc. Ninth Int. Conf. Parallel and Distributed Computing, Applications and Technologies, December 2008, pp. 187-194
4. Wang, Y., Cui, H., Guo, Q., Shu, M.: 'Obstacle-avoidance path planning of a mobile beacon for localization', IET Wirel. Sensor Syst., 2013, 3, (2), pp. 126-137
5. Rasool, I., Kemp, A.H.: 'Statistical analysis of wireless sensor network Gaussian range estimation errors', IET Wirel. Sensor Syst., 2013, 3, (1), pp. 57-68
6. Roufarshbaf, H., Castro, J., Schwaner, F., Abedi, A.: 'Sub-optimum fast Bayesian techniques for joint leak detection and localisation', IET Wirel. Sensor Syst., 2013, 3, (3), pp. 239-246
7. Liu, K., Yan, X., Hu, F.: 'A modified DV-hop localization algorithm for wireless sensor networks'. Proc. 2009 IEEE Int. Conf. Intelligent Computing and Intelligent Systems, November 2009, vol. 3, pp. 511-514
8. Bao, X., Bao, F., Zhang, S., Liu, L.: 'An improved DV-hop localization algorithm for wireless sensor networks'. Proc. Sixth Int. Conf. Wireless Communications Networking and Mobile Computing, September 2010, pp. 1-4
9. Yedavalli, K., Krishnamachari, B., Ravula, S., Srinivasan, B.: 'Ecolocation: a sequence based technique for RF localization in wireless sensor networks'. Proc. Fourth Int. Symp. Information Processing in Sensor Networks, 2005, Article No. 38
10. Kalman, R.E.: 'A new approach to linear filtering and prediction problems', Trans. ASME-J. Basic Eng., 1960, 82, pp. 35-45
11. Chenna, S.K., Jain, Y.K., Kapoor, H., et al.: 'State estimation and tracking problems: a comparison between Kalman filter and recurrent neural networks'. Proc. 2004 Int. Conf. Neural Information Processing, 2004, pp. 275-281
12. Shareef, A., Zhu, Y.F., Musavi, M., Shen, B.: 'Comparison of MLP neural network and Kalman filter for localization in wireless sensor networks'. Proc. 19th IASTED Int. Conf. Parallel and Distributed Computing and Systems, 2007, pp. 323-330
13. Yuan, J., Yu, S.: 'Privacy preserving back-propagation neural network learning made practical with cloud computing', IEEE Trans. Parallel and Distributed Syst., 2014, 25 (1) pp. 212-221
14. Dijkstra, E.: 'A note on two problems in connexion with graphs', Numer. Math., 1959, 1, pp. 269-271
15. Rahman, M.S., Park, Y., Kim, K.-D.: 'RSS-based indoor localization algorithm for wireless sensor network using generalized regression neural network', Arabian J. Sci. Eng., 2012, 37, (4), pp. 1043-1053
16. Irfan, N., Bolic, M., Yagoub, M.C.E., Narasimhan, V.: 'Neural-based approach for localization of sensors in indoor environment', Telecommun. Syst., 2010, 44, (1-2), pp. 149-158
17. Zhang, T., He, J., Zhang, Y.: 'Secure sensor localization in wireless sensor networks based on neural network', Int. J. Comput. Intell. Syst., 2012, 5, (5), pp. 914-923
18. Gholami, M., Cai, N., Brennan, R.W.: 'An artificial neural network approach to the problem of wireless sensors network localization', Robot. Comput. Integr. Manuf., 2013, 29, (1), pp. 96-109
19. Li, S., Qin, F.: 'A dynamic neural network approach for solving nonlinear inequalities defined on a graph and its application to distributed, routing-free, range-free localization of WSNs', Neurocomputing, 2013, 117, pp. 72-80
20. Leung, C.S., Sum, J., So, H.C., Constantinides, A.G., Chan, F.K.W.: 'Lagrange programming neural networks for time-of-arrival-based source localization', Neural Comput. Appl.,2014, 24 (1) pp. 109-116