Hamiltonian properties on the class of hypercube-like networks
Information Processing Letters - Devoted to the rapid publication of short contributions to information processing
Fault-Hamiltonicity of Hypercube-Like Interconnection Networks
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Many-to-Many Disjoint Path Covers in Hypercube-Like Interconnection Networks with Faulty Elements
IEEE Transactions on Parallel and Distributed Systems
Panconnectivity and pancyclicity of hypercube-like interconnection networks with faulty elements
Theoretical Computer Science
The Journal of Supercomputing
Fault-Tolerant Hamiltonicity of Augmented Cubes under the Conditional Fault Model
ICA3PP '09 Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing
Conditional edge-fault Hamiltonicity of augmented cubes
Information Sciences: an International Journal
Information Sciences: an International Journal
Möbius-deBruijn: The product of Möbius cube and deBruijn digraph
Information Processing Letters
{2,3}-Extraconnectivities of hypercube-like networks
Journal of Computer and System Sciences
KMcube: the compound of Kautz digraph and Möbius cube
Frontiers of Computer Science: Selected Publications from Chinese Universities
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The Mcube network proposed in this paper is a highly recursive and symmetrical interconnection network based on twisted links (Abraham and Padmanabhan, 1989). However, unlike other twist-based networks which are asymmetrical, the Mcube has a uniform distance distribution. In addition the Mcube is immune to the adverse effects of skewed traffic patterns that occur in asymmetrical structures. Mcubes have about half the diameter of a hypercube with the same node and link complexity. Mcubes have been defined in terms of the structure of components rather than relations between binary strings chiefly to ensure structural symmetry. Mcubes have a lower average internode distance than other twist-based networks. Reduced network congestion and low message delays allow Mcubes to perform significantly better than other comparable networks particularly under heavy traffic loads. Mcubes can emulate comparable hypercubes with a small routing overhead. Several classes of parallel algorithms can be mapped to execute faster on Mcubes than on hypercubes.