An adaptive system-level diagnosis approach for hypercube multiprocessors

This paper proposes a hierarchical adaptive system-level diagnosis approach for hypercube systems. Three measures for diagnosis cost (diagnosis time, number of tests and number of test links) are analyzed for the proposed algorithm. It is proved that the diagnosis cost required by this algorithm is lower than in the previous diagnosis algorithms in most of the fault cases. It is shown that the diagnosis cost for the proposed algorithm depends on the number of faulty units in the system and the cost is extremely low when only a small number of faulty units exist. It is shown that this algorithm is even characterized by lower costs than a pessimistic diagnosis algorithm which trades lower diagnosis cost for a lower degree of accuracy