Pancake graphs: Structural properties and conditional diagnosability
Nai-Wen Chang (),
Hsuan-Jung Wu () and
Sun-Yuan Hsieh ()
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Nai-Wen Chang: National Cheng Kung University
Hsuan-Jung Wu: National Cheng Kung University
Sun-Yuan Hsieh: National Cheng Kung University
Journal of Combinatorial Optimization, 2022, vol. 44, issue 5, No 5, 3263-3293
Abstract:
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 .
Keywords: Interconnection networks; PMC diagnosis model; Conditional diagnosability; Pancake graphs; Fault tolerance; Multiprocessor systems (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10878-022-00877-8
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