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DOI: 10.14569/IJACSA.2016.070319
PDF

Clustering Analysis of Wireless Sensor Network Based on Network Coding with Low-Density Parity Check

Author 1: Maria Hammouti
Author 2: El Miloud Ar-reyouchi
Author 3: Kamal Ghoumid
Author 4: Ahmed Lichioui

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 3, 2016.

  • Abstract and Keywords
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Abstract: The number of nodes in wireless sensor networks (WSNs) is one of the fundamental parameters when it comes to developing an algorithm based on Network Coding (NC) with LDPC (Low Density Parity Check) code because it directly affects the size of the generator matrix of the LDPC code and to its dispersion. Optimizing Wireless Communication Systems by decreasing BER (Bit Error Rate) is one approach to analyze the network into clusters (at the level of their nodes). In this paper, the authors present a fully distributed clustering algorithm and they consider different node values by cluster, then they select the curves that have the best compromise. They examine the effects of SNR (Signal-to-noise ratio) quantization on system performance obtained for different scenarios (by varying the parameter corresponding to the number of the symbol during the forwarding phase). Finally, the results prove that the increased number nodes improve LDPC code properties.

Keywords: Clustering Techniques; Network Coding; LDPC codes; distributed algorithms; wireless sensor network

Maria Hammouti, El Miloud Ar-reyouchi, Kamal Ghoumid and Ahmed Lichioui, “Clustering Analysis of Wireless Sensor Network Based on Network Coding with Low-Density Parity Check” International Journal of Advanced Computer Science and Applications(IJACSA), 7(3), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070319

@article{Hammouti2016,
title = {Clustering Analysis of Wireless Sensor Network Based on Network Coding with Low-Density Parity Check},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070319},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070319},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {3},
author = {Maria Hammouti and El Miloud Ar-reyouchi and Kamal Ghoumid and Ahmed Lichioui}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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