Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)

Perceptron-based AOW Clustering Algorithms

Authors
Huozhu Wang, Jianguo Yu
Corresponding Author
Huozhu Wang
Available Online April 2016.
DOI
10.2991/ameii-16.2016.244How to use a DOI?
Keywords
Clustering Algorithms, Ad hoc network, adaptive on-demand weighted algorithm,
Abstract

Clustering Algorithms has been widely used in Ad hoc network with its ability to construct network quickly, conveniently and flexibly and without the need of default network infrastructure. In this paper, Firstly, some shortcomings of the typical algorithm AOW (adaptive on-demand weighted algorithm) are introduced and analyzed. Then, we discusses the calculating method of nodes weights with perceptron algorithm and the cluster heads selecting process with modified algorithms based on original AOW to meet system requirements. So, a adaptive on-demand weighted algorithm based perceptron ( PerAOW ) is proposed to select cluster heads in Ad hoc network. Compared to AOW, simulation results proved that the proposed algorithm are improving network topological structure and giving 5.2% better load balance factor ( LBF ).

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
Series
Advances in Engineering Research
Publication Date
April 2016
ISBN
10.2991/ameii-16.2016.244
ISSN
2352-5401
DOI
10.2991/ameii-16.2016.244How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Huozhu Wang
AU  - Jianguo Yu
PY  - 2016/04
DA  - 2016/04
TI  - Perceptron-based AOW Clustering Algorithms
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.244
DO  - 10.2991/ameii-16.2016.244
ID  - Wang2016/04
ER  -