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Open Physics

formerly Central European Journal of Physics

Editor-in-Chief: Feng, Jonathan

Managing Editor: Lesna-Szreter, Paulina

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IMPACT FACTOR 2016 (Open Physics): 0.745
IMPACT FACTOR 2016 (Central European Journal of Physics): 0.765

CiteScore 2016: 0.82

SCImago Journal Rank (SJR) 2015: 0.458
Source Normalized Impact per Paper (SNIP) 2015: 1.142

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ISSN
2391-5471
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Volume 11, Issue 12 (Dec 2013)

Issues

Structural changes in data communication in wireless sensor networks

Raquel Silva Cabral
  • Graduate Program in Electrical Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, 31270-901, Belo Horizonte, MG, Brazil
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/ Andre Aquino
  • Scientific Computing and Numerical Analysis Laboratory, Federal University of Alagoas, Av. Lourival Melo Mota, s/n, 57072-900, Maceió, AL, Brazil
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/ Alejandro Frery
  • Scientific Computing and Numerical Analysis Laboratory, Federal University of Alagoas, Av. Lourival Melo Mota, s/n, 57072-900, Maceió, AL, Brazil
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/ Osvaldo Rosso
  • Scientific Computing and Numerical Analysis Laboratory, Federal University of Alagoas, Av. Lourival Melo Mota, s/n, 57072-900, Maceió, AL, Brazil
  • Complex Systems Laboratory, Engineering Faculty, University of Buenos Aires, Paseo Colón 850, Buenos Aires, Argentina
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/ Jaime Ramírez
  • Graduate Program in Electrical Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, 31270-901, Belo Horizonte, MG, Brazil
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Published Online: 2013-12-20 | DOI: https://doi.org/10.2478/s11534-013-0293-2

Abstract

Wireless sensor networks are an important technology for making distributed autonomous measures in hostile or inaccessible environments. Among the challenges they pose, the way data travel among them is a relevant issue since their structure is quite dynamic. The operational topology of such devices can often be described by complex networks. In this work, we assess the variation of measures commonly employed in the complex networks literature applied to wireless sensor networks. Four data communication strategies were considered: geometric, random, small-world, and scale-free models, along with the shortest path length measure. The sensitivity of this measure was analyzed with respect to the following perturbations: insertion and removal of nodes in the geometric strategy; and insertion, removal and rewiring of links in the other models. The assessment was performed using the normalized Kullback-Leibler divergence and Hellinger distance quantifiers, both deriving from the Information Theory framework. The results reveal that the shortest path length is sensitive to perturbations.

Keywords: complex networks; structural measures; stochastic quantifiers; information theory quantifiers

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About the article

Published Online: 2013-12-20

Published in Print: 2013-12-01


Citation Information: Open Physics, ISSN (Online) 2391-5471, DOI: https://doi.org/10.2478/s11534-013-0293-2.

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