Autosoft Journal

Online Manuscript Access


Energy-Aware Discrete Probabilistic Localization of Wireless Sensor Networks


Authors



Abstract

Localizing sensor nodes is critical in the context of wireless sensor network applications. It has been shown that, for some applications, low-overhead discrete localization achieves results comparable to costly fine localization. This research presents a hybrid energy-aware discrete localization method that requires no transmission overhead from the sensor nodes. The proposed method, E-KalmaNN, is a combination of a Kalman-inspired localization and Artificial Neural Networks estimation that updates the position of a node with respect to a mobile reference. E-KalmaNN runs on the sensor nodes and supports different listening/wakeup frequencies for different nodes to balance power requirements with localization accuracy for each node. Simulation results show that the method converges to the correct position of the node in a relatively short time with high average location accuracy. Compared to the localization methods found in the literature, E-KalmaNN localizes with comparable accuracy, lower transmission costs and/or fewer motion restrictions.


Keywords


Pages

Total Pages: 17
Pages: 407-423

DOI
10.1080/10798587.2013.778053


Manuscript ViewPdf Subscription required to access this document

Obtain access this manuscript in one of the following ways


Already subscribed?

Need information on obtaining a subscription? Personal and institutional subscriptions are available.

Already an author? Have access via email address?


Published

Volume: 19
Issue: 3
Year: 2013

Cite this document


References

Elhajj, I.H. & Gorski, J. Sensor Network and Robot Interaction Using Coarse Localization. (2006). IEEE/RSJ International Conference on Intelligent Robots and Systems. Beijing, China, October

Hu, L. & Evans, D. (2004). Localization for Mobile Sensor Networks. Proc. of the 10

Moore, D., Leonard, J., Rus, D. & Teller, S. (2004). Robust Distributed Network Localization with Noisy Range Measurements. Proc. of the 2

Priyantha, N., Chakraborty, A. & Balakrishnan, H. (2000). The Cricket Location Support System. Proc. of the 6

Galstyan, Aram et al. "Distributed Online Localization in Sensor Networks Using a Moving Target." Proceedings of the third international symposium on Information processing in sensor networks - IPSN”04 (2004): n. pag. Crossref. Web. https://doi.org/10.1145/984622.984632

Priyantha, N., Balakrishnan, H., Demaine, E. & Teller, S. (2003). Anchor-free Distributed Localization in Sensor Networks. Technical Report #892. Cambridge, MA: MIT Laboratory for Computer Science

Savarese, C., Rabaey, J. & Beutel, J. (2001). Locationing in Distributed Ad-hoc Wireless Sensor Networks. Proc. of International Conference on Acoustics, Speech, and Signal Processing

Ramadurai V. Proc. ACM SIGMOBILE Mobile computing and Communications Review 11.1 (2007) https://doi.org/10.1145/1234822.1234823

Xiao, B., Chen, H. & Zhou, S. (2007). A Walking Beacon-Assisted Localization in Wireless Sensor Networks. Proc. of IEEE International Conference, ICC ”07, Glasgow, Scotland, June

Want R. ACM Transactions on Information Systems 10.1 (1992) https://doi.org/10.1145/128756.128759

Reichenbach, F., Blumenthal, J. & Timmermann, D. (2006). Improved Precision of Coarse Grained Localization in Wireless Sensor Networks. Proceedings of the 9

Bulusu N. IEEE Personal Communications Magazine https://doi.org/10.1109/98.878533

Khan Haseebulla M. Proceedings of the 2nd IEEE Workshop on Dependability and Security in Sensor Networks and Systems DSSNS 06

Gorski J. IEEE/ASME International Conference on Advanced Intelligent Mechatronics

Amro, A., Tabboush, A., Krsteva, A. & Elhajj, Imad H. (2008). Discrete Probabilistic Localization for Wireless Sensor Networks. IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Xi”an, China, July 2-5

Kecman V. Learning and Soft Computing Support Vector Machines, Neural Networks, and Fuzzy Logic Models

Karl H. Protocols and Architectures for Wireless Sensor Networks https://doi.org/10.1002/0470095121

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)

TWO YEAR CITATIONS PER DOCUMENT (SJR DATA): 0.993 (2018)
SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."





Journal: 1995-Present


CONTACT INFORMATION


TSI Press
18015 Bullis Hill
San Antonio, TX 78258 USA
PH: 210 479 1022
FAX: 210 479 1048
EMAIL: tsiepress@gmail.com
WEB: http://www.wacong.org/tsi/