scholarly journals Pandemic Metric with Confidence (PMC) Model to Predict Trustworthy Probability of Utilized COVID-19 Pandemic Trajectory across the Global

2021 ◽  
Author(s):  
Zhengkang Zuo ◽  
Lei Yan ◽  
Hongying Zhao
Keyword(s):  
Pmc Model

Adaptive Diagnosis of Hamiltonian Networks under the Comparison Model

2021 ◽  
pp. 2150015
Author(s):  
Wenjun Liu ◽  
Wenjun Li
Keyword(s):  
Fault Diagnosis ◽  
Upper Bound ◽  
Multiprocessor Systems ◽  
Major Goal ◽  
Comparison Model ◽  
A Value ◽  
Pmc Model ◽  
Diagnosis Algorithm ◽  
Test Outcomes

Adaptive diagnosis is an approach in which tests can be scheduled dynamically during the diagnosis process based on the previous test outcomes. Naturally, reducing the number of test rounds as well as the total number of tests is a major goal of an efficient adaptive diagnosis algorithm. The adaptive diagnosis of multiprocessor systems under the PMC model has been widely investigated, while adaptive diagnosis using comparison model has been independently discussed only for three networks, including hypercube, torus, and completely connected networks. In addition, adaptive diagnosis of general Hamiltonian networks is more meaningful than that of special graph. In this paper, the problem of adaptive fault diagnosis in Hamiltonian networks under the comparison model is explored. First, we propose an adaptive diagnostic scheme which takes five to six test rounds. Second, we derive a dynamic upper bound of the number of fault nodes instead of setting a value like normal. Finally, we present an algorithm such that at least one sequence obtained from cycle partition can be picked out and all nodes in this sequence can be identified based on the previous upper bound.

An Exchanged 3-Ary n-Cube Interconnection Network for Parallel Computation

2021 ◽  
pp. 1-18
Author(s):  
Yali Lv ◽  
Cheng-Kuan Lin ◽  
Guijuan Wang
Keyword(s):  
Parallel Computation ◽  
Interconnection Network ◽  
Routing Algorithm ◽  
Small Degree ◽  
Parallel System ◽  
Good Balance ◽  
Pmc Model ◽  
Hardware Costs ◽  
Cube Formula ◽  
Interconnect Network

The interconnetion network plays an important role in a parallel system. To avoid the edge number of the interconnect network scaling rapidly with the increase of dimension and achieve a good balance of hardware costs and properties, this paper presents a new interconnection network called exchanged [Formula: see text]-ary [Formula: see text]-cube ([Formula: see text]). Compared with the [Formula: see text]-ary [Formula: see text]-cube structures, [Formula: see text] shows better performance in terms of many metrics such as small degree and fewer links. In this paper, we first introduce the structure of [Formula: see text] and present some properties of [Formula: see text]; then, we propose a routing algorithm and obtain the diameter of [Formula: see text]. Finally, we analyze the diagnosis of [Formula: see text] and give the diagnosibility under PMC model and MM* model.

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 Matching Composition Networks Under the PMC Model

2009 ◽  
Vol 56 (11) ◽  
pp. 875-879 ◽  
Author(s):  
Min Xu ◽  
K. Thulasiraman ◽  
Xiao-Dong Hu
Keyword(s):  
Pmc Model ◽  
Conditional Diagnosability

Worst-Case Diagnosis Completeness in Regular Graphs under the PMC Model

2007 ◽  
Vol 56 (7) ◽  
pp. 917-9249 ◽  
Author(s):  
Antonio Caruso ◽  
Stefano Chessa ◽  
Piero Maestrini
Keyword(s):  
Regular Graphs ◽  
Worst Case ◽  
Pmc Model ◽  
Case Diagnosis

Connectivity and Nature Diagnosability of Leaf-Sort Graphs

2020 ◽  
Vol 20 (03) ◽  
pp. 2050011
Author(s):  
JUTAO ZHAO ◽  
SHIYING WANG
Keyword(s):  
Interconnection Networks ◽  
Interconnection Network ◽  
Research Topic ◽  
Multiprocessor System ◽  
Important Research ◽  
Edge Connectivity ◽  
Topology Structure ◽  
Pmc Model ◽  
Important Research Topic

The connectivity and diagnosability of a multiprocessor system or an interconnection network is an important research topic. The system and interconnection network has a underlying topology, which usually presented by a graph. As a famous topology structure of interconnection networks, the n-dimensional leaf-sort graph CFn has many good properties. In this paper, we prove that (a) the restricted edge connectivity of CFn (n ≥ 3) is 3n − 5 for odd n and 3n − 6 for even n; (b) CFn (n ≥ 5) is super restricted edge-connected; (c) the nature diagnosability of CFn (n ≥ 4) under the PMC model is 3n − 4 for odd n and 3n − 5 for even n; (d) the nature diagnosability of CFn (n ≥ 5) under the MM* model is 3n − 4 for odd n and 3n − 5 for even n.

scholarly journals The g-Good-Neighbor Diagnosability of Bubble-Sort Graphs under Preparata, Metze, and Chien’s (PMC) Model and Maeng and Malek’s (MM)* Model

Information ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 21
Author(s):  
Shiying Wang ◽  
Zhenhua Wang
Keyword(s):  
Fault Diagnosis ◽  
Interconnection Networks ◽  
Multiprocessor System ◽  
Topology Structure ◽  
Free Node ◽  
Pmc Model ◽  
Good Neighbor

Diagnosability of a multiprocessor system is an important topic of study. A measure for fault diagnosis of the system restrains that every fault-free node has at least g fault-free neighbor vertices, which is called the g-good-neighbor diagnosability of the system. As a famous topology structure of interconnection networks, the n-dimensional bubble-sort graph B n has many good properties. In this paper, we prove that (1) the 1-good-neighbor diagnosability of B n is 2 n − 3 under Preparata, Metze, and Chien’s (PMC) model for n ≥ 4 and Maeng and Malek’s (MM) ∗ model for n ≥ 5 ; (2) the 2-good-neighbor diagnosability of B n is 4 n − 9 under the PMC model and the MM ∗ model for n ≥ 4 ; (3) the 3-good-neighbor diagnosability of B n is 8 n − 25 under the PMC model and the MM ∗ model for n ≥ 7 .

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