Conditional Diagnosability of Alternating Group Networks Under the PMC Model

2020 ◽  
Vol 28 (5) ◽  
pp. 1968-1980
Author(s):  
Nai-Wen Chang ◽  
Sun-Yuan Hsieh
Keyword(s):  
Alternating Group ◽  
Pmc Model ◽  
Conditional Diagnosability

The 1-Good-Neighbor Conditional Diagnosability of Some Regular Graphs

2017 ◽  
Vol 17 (03n04) ◽  
pp. 1741001
Author(s):  
MEI-MEI GU ◽  
RONG-XIA HAO ◽  
AI-MEI YU
Keyword(s):  
Alternating Group ◽  
Regular Graphs ◽  
Connected Graphs ◽  
Free Vertex ◽  
Pmc Model ◽  
Star Networks ◽  
Conditional Diagnosability ◽  
Good Neighbor

The g-good-neighbor conditional diagnosability is the maximum number of faulty vertices a network can guarantee to identify, under the condition that every fault-free vertex has at least g fault-free neighbors. In this paper, we study the 1-good-neighbor conditional diagnosabilities of some general k-regular k-connected graphs G under the PMC model and the MM* model. The main result [Formula: see text] under some conditions is obtained, where l is the maximum number of common neighbors between any two adjacent vertices in G. Moreover, the following results are derived: [Formula: see text] for the hierarchical star networks, [Formula: see text] for the BC networks, [Formula: see text] for the alternating group graphs [Formula: see text].

g-good-neighbor conditional diagnosability of star graph networks under PMC model and MM* model

2017 ◽  
Vol 12 (5) ◽  
pp. 1221-1234 ◽  
Author(s):  
Shiying Wang ◽  
Zhenhua Wang ◽  
Mujiangshan Wang ◽  
Weiping Han
Keyword(s):  
Star Graph ◽  
Pmc Model ◽  
Conditional Diagnosability ◽  
Star Graph Networks ◽  
Good Neighbor

Conditional Diagnosability of Burnt Pancake Networks Under the PMC Model

2015 ◽  
pp. bxv066 ◽  
Author(s):  
Sulin Song ◽  
Shuming Zhou ◽  
Xiaoyan Li
Keyword(s):  
Pmc Model ◽  
Conditional Diagnosability

A Note on the Nature Diagnosability of Alternating Group Graphs Under the PMC Model and MM* Model

2018 ◽  
Vol 18 (01) ◽  
pp. 1850005 ◽  
Author(s):  
SHIYING WANG ◽  
LINGQI ZHAO
Keyword(s):  
Interconnection Networks ◽  
Interconnection Network ◽  
Alternating Group ◽  
Multiprocessor System ◽  
Multiprocessor Systems ◽  
Free Node ◽  
Pmc Model ◽  
Important Study ◽  
Communication Links ◽  
Alternating Group Graph

Many multiprocessor systems have interconnection networks as underlying topologies and an interconnection network is usually represented by a graph where nodes represent processors and links represent communication links between processors. No faulty set can contain all the neighbors of any fault-free node in the system, which is called the nature diagnosability of the system. Diagnosability of a multiprocessor system is one important study topic. As a favorable topology structure of interconnection networks, the n-dimensional alternating group graph AGn has many good properties. In this paper, we prove the following. (1) The nature diagnosability of AGn is 4n − 10 for n − 5 under the PMC model and MM* model. (2) The nature diagnosability of the 4-dimensional alternating group graph AG4 under the PMC model is 5. (3) The nature diagnosability of AG4 under the MM* model is 4.

Sign in / Sign up

Export Citation Format

Share Document