An Efficient Algorithm for Hamiltonian Path Embedding of $k$-Ary $n$-Cubes under the Partitioned Edge Fault Model

Zhuang, Hongbin; Li, Xiao-Yan; Chang, Jou–Ming; Wang, Dajin

doi:10.1109/tpds.2023.3264698

Cited by 5 publications

(1 citation statement)

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“…, Hamiltonian path and Hamiltonian cycle embeddings are important properties because the occurrence of congestion and deadlock can be effectively reduced or even avoided by multi-cast algorithms based on Hamiltonian paths and Hamiltonian cycles [23]. Consequently, there are a great number of research findings on Hamiltonian properties on particular network topologies, such as hypercube [24], cross cube [25,26], twist cube [27][28][29], extended cube [30], k-ary n-cube [31][32][33], and DCell [34,35].…”

Section: Introductionmentioning

confidence: 99%

A Novel Conditional Connectivity and Hamiltonian Connectivity of BCube with Various Faulty Elements

Lin

You

2023

Mathematics

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BCube is one of the main data center networks because it has many attractive features. In practical applications, the failure of components or physical connections is inevitable. In data center networks in particular, switch failures are unavoidable. Fault-tolerance capability is one main aspect to measure the performance of data center networks. Connectivity, fault tolerance Hamiltonian connectivity, and fault tolerance Hamiltonicity are important parameters that assess the fault tolerance of networks. In general, the distribution of fault elements is scattered, and it is necessary to consider the distribution of fault elements in different dimensions. We research the fault tolerance of BCube when considering faulty switches and faulty links/edges that distribute in different dimensions. We also investigate the connectivity, fault tolerance Hamiltonian connectivity, and Hamiltonicity. This study better evaluates the fault-tolerant performance of data center networks.

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