Characterization of Diagnosability Under the Bounded Comparison Model
Qifan Zhang, Shuming Zhou, Sun‐Yuan Hsieh · IEEE Transactions on Reliability · 2024
The$(f_{1},f_{2})$-bounded symmetric comparison ($(f_{1}, f_{2})$-BSC) model, proposed by Fuhrman and Nussbaumer in 1996, is a hybrid of the symmetric comparison model and asymmetric one, which assumes that at most$f_{1}$processors fail while the upper threshold of faulty processors producing identical outcomes is$f_{2}$. Based on the$(f_{1},f_{2})$-BSC model, a novel model, abbreviated as the$f$-BSC model, is proposed by dropping the restriction on$f_{1}$but highlighting the hypothesis on maximum number of faulty processors producing identical outcomes is$f$. As a generalization of this model, a variant of MM$^*$model abbreviated as the$f$-BMM$^*$model is proposed by adding an upper threshold$f$to the number of faulty processors producing identical comparison outcomes, which are executed by a faulty comparator on two faulty neighbouring processors. Under this restriction, fewer possible syndromes are generated and therefore faulty processors can be diagnosed faster and more accurately. Subsequently, we present diverse characterizations regarding system-level diagnosis under the two new models. Moreover, we further establish the metric correlation between$g$-good-neighbor ($g$-GN) diagnosability under$f$-BMM$^*$model and$R^{g}$-connectivity of general networks. Finally, the$g$-GN diagnosabilities under$f$-BMM$^*$model are characterized among five preeminent interconnection networks.