Title

Consensus-Based Evaluation For Fault Isolation And On-Line Evolutionary Regeneration

Abstract

While the fault repair capability of Evolvable Hardware (EH) approaches have been previously demonstrated, further improvements to fault handling capability can be achieved by exploiting population diversity during all phases of the fault handling process. A new paradigm for online EH regeneration using Genetic Algorithms (GAs) called Consensus Based Evaluation (CBE) is developed where the performance of individuals is assessed based on broad consensus of the population instead of a conventional fitness function. Adoption of CBE enables information contained in the population to not only enrich the evolutionary process, but also support fault detection and isolation. On-line regeneration of functionality is achieved without additional test vectors by using the results of competitions between individuals in the population. Relative fitness measures support adaptation of the fitness evaluation procedure to support graceful degredation even in the presence of unpredictable changes in the operational environment, inputs, or the FPGA application. Application of CBE to FPGA-based multipliers demonstrates 100% isolation of randomly injected stuck-at faults and evolution of a complete regeneration within 135 repair iterations while precluding the propagation of any discrepant output. The throughput of the system is maintained at 85.35% throughout the repair process. © Springer-Verlag Berlin Heidelberg 2005.

Publication Date

1-1-2005

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

3637 LNCS

Number of Pages

12-24

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/11549703_2

Socpus ID

33645971660 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33645971660

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