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Information Sciences
Volume 177, Issue 8, 15 April 2007, Pages 1771-1781
 
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doi:10.1016/j.ins.2006.10.002    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2006 Elsevier Inc. All rights reserved.

A (4n − 9)/3 diagnosis algorithm on n-dimensional cube network

Xiaofan YangCorresponding Author Contact Information, a, E-mail The Corresponding Author, E-mail The Corresponding Author and Yuan Yan Tanga

aCollege of Computer Science, Chongqing University, Chongqing 400044, China

Received 26 January 2006; 
revised 31 August 2006; 
accepted 14 October 2006. 
Available online 7 November 2006.

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Abstract

As a generalization of the precise and pessimistic diagnosis strategies of system-level diagnosis of multicomputers, the t/k diagnosis strategy can significantly improve the self-diagnosing capability of a system at the expense of no more than k fault-free processors (nodes) being mistakenly diagnosed as faulty. In the case k greater-or-equal, slanted 2, to our knowledge, there is no known t/k diagnosis algorithm for general diagnosable system or for any specific system. Hypercube is a popular topology for interconnecting processors of multicomputers. It is known that an n-dimensional cube is (4n − 9)/3-diagnosable. This paper addresses the (4n − 9)/3 diagnosis of n-dimensional cube. By exploring the relationship between a largest connected component of the 0-test subgraph of a faulty hypercube and the distribution of the faulty nodes over the network, the fault diagnosis of an n-dimensional cube can be reduced to those of two constituent (n − 1)-dimensional cubes. On this basis, a diagnosis algorithm is presented. Given that there are no more than 4n − 9 faulty nodes, this algorithm can isolate all faulty nodes to within a set in which at most three nodes are fault-free. The proposed algorithm can operate in O(N log2 N) time, where N = 2n is the total number of nodes of the hypercube. The work of this paper provides insight into developing efficient t/k diagnosis algorithms for larger k value and for other types of interconnection networks.

Keywords: Multicomputer; System-level diagnosis; t/k diagnosis algorithm; Hypercube

Article Outline

1. Introduction
2. Preliminaries
2.1. Hypercube
2.2. System-level diagnosis
3. Theory behind the new diagnosis algorithm
4. A diagnosis algorithm
4.1. Formal description of the new diagnosis algorithm
4.2. Correctness
4.3. Time complexity
5. Conclusions
Acknowledgements
Appendix A. Proof of theorem 3.1
References



Information Sciences
Volume 177, Issue 8, 15 April 2007, Pages 1771-1781
 
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