Nodes selection mechanism based on modified binary particle swarm optimization algorithm

DOI

10.2991/icismme-15.2015.414How to use a DOI?

Keywords

wireless sensor networks; node selection; binary particle swarm optimization; penalty function method

Abstract

Considering the problem of nodes selection in multi-target tracking of wireless sensor networks, a modified binary particle swarm optimization with a novel particle encoding method and particle position update rules and a mutation operation. Based on this modified binary particle swarm optimization, a nodes selection mechanism was proposed to maximize measurement information. The penalty function method was used to convert the constraint problem into an unconstrained one. The mechanism exploited the convergence speed and global search ability of the particle swarm optimization algorithm to make the optimization process achieving high-quality solutions in a short period of time. Finally, the experimental results show that the proposed nodes selection mechanism is significantly better than the classical branch and bound algorithm, and satisfies the needs of large-scale network nodes selection.

Copyright

© 2015, 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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TY  - CONF
AU  - Shengyun Wei
AU  - Jing Zhang
AU  - Taichuan Sun
PY  - 2015/07
DA  - 2015/07
TI  - Nodes selection mechanism based on modified binary particle swarm optimization algorithm
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 2008
EP  - 2012
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.414
DO  - 10.2991/icismme-15.2015.414
ID  - Wei2015/07
ER  -