Title :
A Systematic Algorithm for Identifying Faults on Hypercube-Like Networks Under the Comparison Model
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Dong Hwa Univ., Hualien, Taiwan
fDate :
6/1/2012 12:00:00 AM
Abstract :
There is a growing demand for fault diagnosis to increase the reliability of systems. Diagnosis by comparison is a realistic approach to the fault diagnosis of multiprocessor systems. In this paper, we consider n-dimensional hypercube-like networks for n ≥ 5. We propose an efficient fault diagnosis algorithm for n-dimensional hypercube-like networks under the MM comparison model by exploiting the Hamiltonian and extended-star properties. Applying our algorithm, the faulty processors in n-dimensional hypercubes, n-dimensional crossed cubes, n-dimensional twisted cubes, and n-dimensional Möbius cubes can all be diagnosed in linear time provided the number of faulty processors is not more than the dimension n.
Keywords :
fault diagnosis; multiprocessing systems; reliability; Hamiltonian properties; MM comparison model; extended-star properties; fault diagnosis algorithm; fault identification; hypercube-like networks; multiprocessor systems; n-dimensional Mobius cubes; n-dimensional crossed cubes; n-dimensional hypercube-like networks; n-dimensional hypercubes; n-dimensional twisted cubes; systematic algorithm; systems reliability; Complexity theory; Computer network reliability; Decoding; Fault diagnosis; Hypercubes; Program processors; Testing; $t$-diagnosable; Comparison model; Hamiltonian; extended star; hypercube-like networks; linear time algorithm;
Journal_Title :
Reliability, IEEE Transactions on
DOI :
10.1109/TR.2012.2183913