A t/k diagnosis algorithm on hypercube‐like networks

• Published in: Concurrency and computation Vol. 30; no. 6
• Main Authors: Xie, Min, Ye, Liangcheng, Liang, Jiarong
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 25.03.2018
• Subjects: Algorithms; Cubes; Fault diagnosis; Fault tolerance; Hypercubes; hypercube‐like networks; large connected component; Microprocessors; Multiprocessing; Networks; system‐level diagnosis; t/k diagnosis strategy
• ISSN: 1532-0626; 1532-0634
• DOI: 10.1002/cpe.4358

Summary Processor fault diagnosis takes a key role in fault‐tolerant computing on multiprocessor systems. The t/k diagnosis strategy which is a generalization of the precise and pessimistic diagnosis strategies can significantly improve the self‐diagnosing capability of the system. Using this tool, it is possible to deal with large faults in the system. This paper presents a t/k diagnosis algorithm on n‐dimensional hypercube‐like networks (include Hypercubes, Crossed cubes, Möbius cubes, Locally Twisted cubes, and Twisted cubes) for any k∈[0,n−2]. The algorithm can correctly identify all nodes except at most k nodes undiagnosed. It runs in O(N) time, where N=2n is the total number of nodes of n‐dimensional hypercube‐like networks. To the best of our knowledge, in the case k≥4, there is no known t/k diagnosis algorithm for general diagnosable system or any specific system.