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Pancake graphs: Structural properties and conditional diagnosability

Author

Listed:
  • Nai-Wen Chang

    (National Cheng Kung University)

  • Hsuan-Jung Wu

    (National Cheng Kung University)

  • Sun-Yuan Hsieh

    (National Cheng Kung University)

Abstract

Because of the increasing size of multi-processor systems, processor-fault diagnosis has played critical role in measuring reliability. The diagnosability of numerous well-known multiprocessor systems has been widely investigated. The conditional diagnosability is a new measure of diagnosability by restricting an additional condition under which any fault set cannot contain all the neighbors of any node in a system. This study evaluated the conditional diagnosability for pancake graphs in the PMC model. First, several properties of pancake graphs were derived and, based on these properties, the conditional diagnosability of an n-dimensional pancake graph was shown to be 2 for $$n=3$$ n = 3 and $$8n-21$$ 8 n - 21 for $$n\ge 4$$ n ≥ 4 .

Suggested Citation

  • Nai-Wen Chang & Hsuan-Jung Wu & Sun-Yuan Hsieh, 2022. "Pancake graphs: Structural properties and conditional diagnosability," Journal of Combinatorial Optimization, Springer, vol. 44(5), pages 3263-3293, December.
    • Handle: RePEc:spr:jcomop:v:44:y:2022:i:5:d:10.1007_s10878-022-00877-8
    DOI: 10.1007/s10878-022-00877-8
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