4.6 Article

A Comparison Fault Diagnosis Algorithm for Star Networks

Journal

IEEE ACCESS
Volume 9, Issue -, Pages 94214-94223

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3093335

Keywords

Fault diagnosis; star network; Hamiltonian cycle; the comparison model; multiprocessor system

Funding

  1. Natural Science Foundation of China [61862003, 61761006]
  2. Natural Science Foundation of the Guangxi Zhuang Autonomous Region of China [2018GXNSFDA281052]

Ask authors/readers for more resources

The paper proposes a precise fault diagnosis algorithm for a star network system, consisting of three main parts. The theoretical analysis and simulation results demonstrate the accuracy and time complexity of the algorithm.
Fault diagnosis for a multiprocessor system is a process of identifying the faulty nodes in the system and is an important issue on the reliability of the system. As to the problem that there are few effective algorithms to diagnose faulty nodes in a given star network system in the literature, this paper proposes a precise fault diagnosis algorithm to identify faulty nodes in a star network system with a given syndrome under the comparison model. Such an algorithm contains three main parts. In the first part, we present an algorithm called Partition-Cycle for partitioning a cycle into sequences based on a given syndrome of the cycle. In the second part, we introduce an algorithm called Digout to diagnose these cycle sequences obtained the first part, which can diagnose each node in the cycle to be faulty or fault-free or unknown. In the third part, we design a diagnosis algorithm called Star-Digout to diagnose faulty nodes in an n-dimensional (n >= 6) star networks, which is proved to contain a cycle that contains all nodes in the network and is not the same two nodes. Our theoretical analysis shows the time complexity of the diagnosis algorithm isO(n!). Our simulation results show that our algorithm is a precise diagnosis algorithm for a star network system.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available