Multi-domain Cooperative Service Fault Diagnosis Algorithm Under Network Slicing with Software Defined Networks

2021 ◽  
pp. 55-64
Author(s):  
Wei Li ◽  
Yong Dai ◽  
Yong Xu ◽  
Xilao Wu ◽  
Wei Li ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Software Defined Networks ◽  
Network Slicing ◽  
Diagnosis Algorithm

Diagnostic Fault Simulation for the Failure Analyst

2004 ◽  
Author(s):  
Dan Bodoh ◽  
Anthony Blakely ◽  
Terry Garyet
Keyword(s):  
Fault Diagnosis ◽  
Failure Analysis ◽  
Complete Solution ◽  
Fault Simulation ◽  
Building Blocks ◽  
Physical World ◽  
Design For Test ◽  
Fault Diagnosis System ◽  
Diagnosis Algorithm ◽  
Diagnosis Tool

Abstract Since failure analysis (FA) tools originated in the design-for-test (DFT) realm, most have abstractions that reflect a designer's viewpoint. These abstractions prevent easy application of diagnosis results in the physical world of the FA lab. This article presents a fault diagnosis system, DFS/FA, which bridges the DFT and FA worlds. First, it describes the motivation for building DFS/FA and how it is an improvement over off-the-shelf tools and explains the DFS/FA building blocks on which the diagnosis tool depends. The article then discusses the diagnosis algorithm in detail and provides an overview of some of the supporting tools that make DFS/FA a complete solution for FA. It also presents a FA example where DFS/FA has been applied. The example demonstrates how the consideration of physical proximity improves the accuracy without sacrificing precision.

Efficient Fault Diagnosis Algorithm in Dynamic Internet Service Environment

2009 ◽  
Vol 20 (9) ◽  
pp. 2520-2530
Author(s):  
Ling-Wei CHU ◽  
Shi-Hong ZOU ◽  
Shi-Duan CHENG ◽  
Chun-Qi TIAN ◽  
Wen-Dong WANG
Keyword(s):  
Fault Diagnosis ◽  
Internet Service ◽  
Service Environment ◽  
Diagnosis Algorithm

Orthotopic-filtering-based hierarchical fault diagnosis algorithm for linear recursive models

2020 ◽  
Vol 14 (16) ◽  
pp. 2310-2318
Author(s):  
Ziyun Wang ◽  
Guixiang Xu ◽  
Yan Wang ◽  
Ju H. Park ◽  
Zhicheng Ji
Keyword(s):  
Fault Diagnosis ◽  
Recursive Models ◽  
Diagnosis Algorithm

scholarly journals A Fault Diagnosis Algorithm for Wind Turbine Blades Based on BP Neural Network

2021 ◽  
Vol 1043 (2) ◽  
pp. 022032
Author(s):  
Jun-Xi Bi ◽  
Wen-Ze Fan ◽  
Ying Wang ◽  
Jun Ren ◽  
Hai-Bin Li
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Wind Turbine ◽  
Bp Neural Network ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Diagnosis Algorithm

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.

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