Abstract
AI-based search techniques have been adapted as viable, topology-independent fault-tolerant routing strategies on multiprocessor networks [P.K.K. Loh, Artificial intelligence search techniques as fault-tolerant routing strategies, Parallel Computing 22 (8) (1996) 1127–1147]. These fault-tolerant routing strategies are viable with the exception that the routes obtained were non-minimal. This meant that a large number of redundant node traversals were made in reaching the destination, increasing the likelihood of encountering further faulty network components. Here, we investigate the adaptation of a genetic-heuristic algorithm combination as a fault-tolerant routing strategy. Our results show that this hybrid fault-tolerant routing strategy produces minimal or near-minimal routes. Under certain fault conditions, this new strategy outperforms the heuristic AI-based ones with a significant reduction in the number of redundant traversals.
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