Conditional (t,k)-Diagnosis in Graphs by Using the Comparison Diagnosis Model
Chun-An Chen, Guey-Yun Chang, Sun‐Yuan Hsieh · IEEE Transactions on Computers · 2014
(t, k)-Diagnosis, which is a generalization of sequential diagnosis, requires that at least k faulty processors be identified and repaired in each iteration when there are at most t faulty processors, where t ≥ k. Based on the assumption that each vertex is adjacent to at least one fault-free vertex, the conditional (t, k)-diagnosis of graphs was investigated by using the comparison diagnosis model. Lower bounds on the conditional (t, k)-diagnosability of graphs were derived, and applied to obtain the following results. 1) Symmetric d-dimensional grids are conditionally (N/2d+1 -1, 2d -1)-diagnosable when d ≥ 2 and N (the number of vertices) ≥ 4d. 2) Symmetric d-dimensional tori are conditionally (1/5 (N + min{8/5 N2/3, 2N-20/15} - 2), 6)-diagnosable when d = 2 and N ≥ 49 and ( N/2d+1 -1, 4d-2)-diagnosable when d ≥ 3 and N ≤ 4d. 3) Cube-connected cycles are conditionally (N/4 - 1, 4)-diagnosable. 4) k-ary trees are conditionally (N/k+1 - 1)-diagnosable.