Abstract
Most fault-tolerant routing strategies are topology dependent or constrained to tolerate specific classes of faults. Artificial Intelligence search techniques, on the other hand, are potentially adaptive and can be applied to a generic problem space. We investigate the performance of such search techniques modified for use as fault-tolerant routing strategies on a problem space simulating a multiprocessor network of generic topology. This virtual network comprises processors individually equipped with a communications router designed to support message routing. The performances of these modified search techniques are compared for up to 20% of randomly generated link faults (with a processor failure being simulated by total link failure). The results show that the heuristic class of search techniques are potentially suitable for adaptation as fault-tolerant routing strategies on multiprocessor networks.
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