Multi-Objective Evolutionary Optimizations of a Space-Based Reconfigurable Sensor Network under Hard Constraints

Authors:
Erfu Yang;Ahmet T. Erdogan;Tughrul Arslan;Nick Barton
Affiliations:
The University of Edinburgh, United Kingdom;The University of Edinburgh, United Kingdom;The University of Edinburgh, United Kingdom;The University of Edinburgh, United Kingdom
Venue:
BLISS '07 Proceedings of the 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security
Year:
2007

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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 multi-criteria solutions in the sense of Pareto 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.