Fault tolerant three-dimensional cellular genetic algorithms with adaptive migration schemes

This paper presents a three-dimensional cellular genetic algorithm (3D-cGA) to achieve fault tolerance; in particular, faults occurred due to single event upsets (SEUs). Cellular genetic algorithms (cGAs) are targeted due to their high performance and inherent features, among others. Genetic diversity is the main factor in identifying and isolating faults occurred, particularly at individuals' phenotypes. This type of failure could affect system functionality, and thus, fault tolerant design approaches at an algorithm level, such as the approach proposed, are targeted nowadays. We consider the GPS attitude determination as a case study to investigate the effectiveness of the proposed 3D-cGA. The overall results show success in handling up to 40% faults. In order to alleviate the deterioration in the performance of the algorithm, we propose a number of adaptive migration schemes. The different schemes are tested to show superior improvements in the algorithm's performance in terms of efficiency, efficacy, and speed.

[1]  Marco Tomassini,et al.  Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time (Natural Computing Series) , 2005 .

[2]  Matthew French,et al.  Tolerating SEU Faults in the Raw Architecture , 2006 .

[3]  Anantha Chandrakasan,et al.  Three-dimensional integrated circuits: performance, design methodology, and CAD tools , 2003, IEEE Computer Society Annual Symposium on VLSI, 2003. Proceedings..

[4]  Enrique Alba,et al.  The exploration/exploitation tradeoff in dynamic cellular genetic algorithms , 2005, IEEE Transactions on Evolutionary Computation.

[5]  Tughrul Arslan,et al.  GPS attitude determination using a genetic algorithm , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[6]  Rasmus K. Ursem,et al.  Diversity-Guided Evolutionary Algorithms , 2002, PPSN.

[7]  Tughrul Arslan,et al.  Towards Fault-Tolerant Systems based on Adaptive Cellular Genetic Algorithms , 2008, 2008 NASA/ESA Conference on Adaptive Hardware and Systems.

[8]  F. Faure,et al.  How to characterize the problem of SEU in processors & representative errors observed on flight , 2005, 11th IEEE International On-Line Testing Symposium.

[9]  Sven E. Eklund,et al.  A massively parallel architecture for distributed genetic algorithms , 2004, Parallel Comput..

[10]  Tughrul Arslan,et al.  Fault Tolerant and Adaptive GPS Attitude Determination System , 2009, 2009 IEEE Aerospace conference.

[11]  L. Darrell Whitley,et al.  Cellular Genetic Algorithms , 1993, ICGA.

[12]  Erick Cantú-Paz,et al.  A Summary of Research on Parallel Genetic Algorithms , 1995 .

[13]  Thomas Bäck,et al.  Using a genetic algorithm to evolve behavior in multi dimensional cellular automata: emergence of behavior , 2005, GECCO '05.

[14]  Tughrul Arslan,et al.  Towards 3D Architectures: A Comparative Study on Cellular GAs Dimensionality , 2009, 2009 NASA/ESA Conference on Adaptive Hardware and Systems.

[15]  Tughrul Arslan,et al.  Fault tolerant cellular Genetic Algorithm , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[16]  Tughrul Arslan,et al.  Fault tolerance through automatic cell isolation using three-dimensional cellular genetic algorithms , 2010, IEEE Congress on Evolutionary Computation.

[17]  Fang Liu,et al.  A New Approach to Single Event Effect Tolerance Based on Asynchronous Circuit Technique , 2008, J. Electron. Test..