Fault tolerance through automatic cell isolation using three-dimensional cellular genetic algorithms

In this paper we propose a new algorithmic approach to achieve fault tolerance based on three dimensional cellular genetic algorithms (3D-cGAs). Herein, 3D architecture is targeted due to its amenability to implementation with current advanced custom silicon chip technology. The proposed approach is designed to exploit the inherent features of a cGA in which the genetic diversity is used as the key factor in identifying and isolating faulty individuals. A new migration schema is proposed as a mitigation technique. Several configurations concerning migration and selection intensity are considered. The approach is tested using four benchmark test functions and two real world problems which present different levels of difficulty. The overall results show that the proposed approach is able to cope with up to 40% soft errors (SEUs).