Multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints

Tools

Yang, Erfu and Erdogan, Ahmet T. and Arslan, Tughrul and Barton, Nick; (2007) Multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints. In: ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, 2007. BLISS 2007. IEEE, GBR, pp. 72-75. ISBN 0-7695-2919-4 (https://doi.org/10.1109/BLISS.2007.20)

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Abstract

Wireless sensor networks have emerged as a promising way to develop high security systems. This paper presents the optimizations of a space-based reconfigurable sensor network under hard constraints by employing an efficient multi-objective evolutionary algorithm (MOEA). First, a system model is proposed for cluster-based space wireless sensor networks. Second, the statement of multi-objective optimization problems is mathematically formulated under multiple constraints. Third, the MOEA is used to find multicriteria solutions in the sense of Parelo optimizations. Finally, simulation results are provided to illustrate the effectiveness of applying the MOEA to the multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints.

ORCID iDs

Yang, Erfu ORCID logoORCID: https://orcid.org/0000-0003-1813-5950, Erdogan, Ahmet T., Arslan, Tughrul and Barton, Nick;
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