Adaptive Fault Diagnosis using Syndrome Analysis for Hypercube Network 


Vol. 31,  No. 8, pp. 701-706, Aug.  2006


PDF Full-Text
  Abstract

System-level diagnosis plays an important technique for fault detection in multi-processor systems. Efficient diagnosis is very important for real timesystems as well as multiprocessor systems. Feng[1] proposed two adaptive diagnosis algorithms HADA and IHADA for hypercube system. The diagnosis cost, measured by diagnosis time and the number of test links, depends on the number and locaton of the faults. In this paper, we propose an adaptive diagnosis algorithm using the syndrome analysis. This removes unnecessary overhead generated in HADA and IHADA algorithmsand give a better performance compared to Feng’s Method.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Cite this article

[IEEE Style]

J. Kim and C. Rhee, "Adaptive Fault Diagnosis using Syndrome Analysis for Hypercube Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 31, no. 8, pp. 701-706, 2006. DOI: .

[ACM Style]

Jang-Hwan Kim and Chung-Sei Rhee. 2006. Adaptive Fault Diagnosis using Syndrome Analysis for Hypercube Network. The Journal of Korean Institute of Communications and Information Sciences, 31, 8, (2006), 701-706. DOI: .

[KICS Style]

Jang-Hwan Kim and Chung-Sei Rhee, "Adaptive Fault Diagnosis using Syndrome Analysis for Hypercube Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 31, no. 8, pp. 701-706, 8. 2006.

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)






pISSN : 1226 - 4717
eISSN : 2287 - 3880