【Relating Diagnosability, Strong Diagnosability and Conditional Diagnosability of Strong Networks】
时间：2013年7月11日(星期四) 下午 14:30
地点：成功楼603教室
主讲：西安电子科技大学 朱 强 副教授
主办：数计学院
Abstract: An interconnection network’s Diagnosabilityis an important measure of its self-diagnostic capability. Based on the classical notion of diagnosability, strong diagnosability and Conditio-
nnal diagnosability were proposed later to better reflect the networks’ self-diagnostic cap-
ability under more realistic assumptions. In this paper, we study a class of interconnection
networks called strong networks. We build a relationship amongst the three diagnosability
measures for strong networks: Under both PMC and MM models, given a strong network G
with diagnosability t, we prove that G is strongly t-diagnosable if and only if G’s condition-
nal diagnosability is greater than t. A simple check can show that almost all well-known re-
gular interconnection networks are strong networks. The significance of this paper’s result
is that it reveals an important relationship between strong and conditional diagnosabilities,
and the proof of strong diagnosability for many interconnection networks under MM or PM-
C model is not necessary if their conditional diagnosability can be shown to be strictly larg-
er than their diagnosability.
