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Open Access research with a European policy impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the European Policies Research Centre (EPRC).

EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

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An adaptive approach to space-based picosatellite sensor networks

Arslan, Tughrul and Yang, Erfu and Haridas, Nakul and Morales, Alicia and El-Rayis, Ahmed O. and Erdogan, Ahmet T. and Stoica, Adrian (2009) An adaptive approach to space-based picosatellite sensor networks. In: Evolutionary and Bio-Inspired Computation. Proceedings of SPIE . SPIE Press, Bellingham, Washington. ISBN 9780819476135

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Abstract

The rapid advancements in ad hoc sensor networks, MEMS (micro-electro- mechanical systems) devices, low-power electronics, adaptive hardware and systems (AHS), reconfigurable architectures, high-performance computing platforms, distributed operating systems, micro-spacecrafts, and micro-sensors have enabled the design and development of a highperformance satellite sensor network (SSN). Due to the changing environment and the varying missions that a SSN may have, there is an increasing need to develop efficient strategies to design, operate, and manage the system at different levels from an individual satellite node to the whole network. Towards this end, this paper presents an adaptive approach to space-based picosatellite sensor network by exploiting efficient bio-inspired optimization algorithms, particularly for solving multi-objective optimization problems at both local (node) and global (network) system levels. The proposed approach can be hierarchically used for dealing with the challenging optimization problems arising from the energy-constrained satellite sensor networks. Simulation results are provided to demonstrate the effectiveness of the proposed approach through its application in solving both node-level and system-level optimization problems.