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Localization Adopting Machine Learning Techniques in Wireless Sensor Networks

S. Pandey1

  1. Dept. of Computer Science and Engineering, Kamla Nehru Institute of Technology, Sultanpur, India.

Correspondence should be addressed to: sumanuptu@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-1 , Page no. 366-374, Jan-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i1.366374

Online published on Jan 31, 2018

Copyright © S. Pandey . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S. Pandey, “Localization Adopting Machine Learning Techniques in Wireless Sensor Networks,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.366-374, 2018.

MLA Style Citation: S. Pandey "Localization Adopting Machine Learning Techniques in Wireless Sensor Networks." International Journal of Computer Sciences and Engineering 6.1 (2018): 366-374.

APA Style Citation: S. Pandey, (2018). Localization Adopting Machine Learning Techniques in Wireless Sensor Networks. International Journal of Computer Sciences and Engineering, 6(1), 366-374.

BibTex Style Citation:
@article{Pandey_2018,
author = {S. Pandey},
title = {Localization Adopting Machine Learning Techniques in Wireless Sensor Networks},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2018},
volume = {6},
Issue = {1},
month = {1},
year = {2018},
issn = {2347-2693},
pages = {366-374},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1686},
doi = {https://doi.org/10.26438/ijcse/v6i1.366374}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i1.366374}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1686
TI - Localization Adopting Machine Learning Techniques in Wireless Sensor Networks
T2 - International Journal of Computer Sciences and Engineering
AU - S. Pandey
PY - 2018
DA - 2018/01/31
PB - IJCSE, Indore, INDIA
SP - 366-374
IS - 1
VL - 6
SN - 2347-2693
ER -

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Abstract

Monitoring of dynamic environments that change rapidly with time is the prime application of wireless sensor networks. This change of behaviour is reasoned to either certain external factors or limitation of system designs itself in unpredicted causality. To adapt such conditions, machine learning techniques are deemed to be beneficial in eliminating the need for unnecessary redesign. Moreover, the techniques based on machine learning encourages many practical solutions to maximize usages of resource and thus enhances the lifespan of the sensor network. In this paper, an extensive literature is furnished over machine learning techniques that are used to address the issue of node localization in wireless sensor networks (WSNs). Strengths and weaknesses of each of the proposed algorithm in literature have been analysed and evaluated against the problem it has been developed. A comparative table is also presented to guide future designers in developing machine learning solutions suitable for specific application challenges in localization.

Key-Words / Index Term

Wireless sensor networks, machine learning, localization, clustering, data aggregation

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