Multiobjective Optimal Design of MEMS-Based Reconfigurable and Evolvable Sensor Networks for Space Applications

Authors:
Erfu Yang;Nakul Haridas;A. El-Rayis;A. T. Erdogan;Tughrul Arslan;Nick Barton
Affiliations:
University of Edinburgh;University of Edinburgh;University of Edinburgh;University of Edinburgh;University of Edinburgh;University of Edinburgh
Venue:
AHS '07 Proceedings of the Second NASA/ESA Conference on Adaptive Hardware and Systems
Year:
2007

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Scalability of a Novel Shifting Balance Theory-Based Optimization Algorithm: A Comparative Study on a Cluster-Based Wireless Sensor Network

ICES '08 Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware

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Abstract

In this paper, the multiobjective optimal design of spacebased reconfigurable sensor networks with novel adaptive MEMS antennas is investigated by using multiobjective evolutionary algorithms. The non-dominated sorting genetic algorithm II (NSGA-II) is employed to obtain multi-criteria Pareto-optimal solutions, which allows system designers to easily make a reasonable trade-off choice from the set of non-dominated solutions according to their preferences and system requirements. As a case study, a cluster-based satellite sensing network is simulated under multiple objectives. Most importantly, this paper also presents the application of our newly designed adaptive MEMS antennas together with the NSGA-II to the multiobjective optimal design of space-based reconfigurable sensor networks.