On g-extra conditional diagnosability of hierarchical cubic networks

Liu, Huiqing; Zhang, Shunzhe; Dong, Li Hua

doi:10.1016/j.tcs.2019.04.028

Cited by 14 publications

(2 citation statements)

References 28 publications

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“…Since failures of processors and links are inevitable in multiprocessor systems, fault tolerance is an important issue in interconnection networks. Fault tolerance of interconnection networks becomes an essential problem and has been widely studied, such as, structure connectivity and substructure connectivity of hypercubes [20], extra connectivity of bubble sort star graphs [10], g-extra conditional diagnosability of hierarchical cubic networks [21], g-good-neighbor connectivity of graphs [25], conditional connectivity of Cayley graphs generated by unicyclic graphs [26].…”

Section: Introductionmentioning

confidence: 99%

Component (edge) connectivity of pancake graphs

Hua

2023

Ars Math. Contemp.

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Section: Introductionmentioning

confidence: 99%

Component (edge) connectivity of pancake graphs

Hua

2023

Ars Math. Contemp.

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“…Because of their important role in both network theory and practice, many diagnosability results have appeared in literature. Recent examples include g-extra diagnosability results for the hypercube [58], the arrangement graph [44], the bubble-sort graph [48], the (n, k)-star graph [37], and the hierarchical cubic network [36], all in terms of both PMC and/or MM* models. We notice that much of the ad hoc derivation details, as reported in those papers devoted to different structures are essentially shared among themselves, and even with the results on the g-good-neighbor diagnosability derived for these structures [13,40,45,47,50,52].…”

Section: Introductionmentioning

confidence: 99%

A general approach to deriving diagnosability results of interconnection networks*

Cheng

Mao

Qiu

et al. 2022

International Journal of Parallel, Emergent and Distributed Sys

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We generalize an approach to deriving diagnosability results of various interconnection networks in terms of the popular g-good-neighbor and g-extra fault-tolerant models, as well as mainstream diagnostic models such as the PMC and the MM* models.As demonstrative examples, we show how to follow this constructive, and effective, process to derive the g-extra diagnosabilities of the hypercube, the (n, k)-star, and the arrangement graph. These results agree with those achieved individually, without duplicating structure independent technical details. Some of them come with a larger applicable range than those already known, and the result for the arrangement graph in terms of the MM* model is new.

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Lower bounds for dilation, wirelength, and edge congestion of embedding graphs into hypercubes

et al. 2020

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Interconnection networks provide an effective mechanism for exchanging data between processors in a parallel computing system. One of the most efficient interconnection networks is the hypercube due to its structural regularity, potential for parallel computation of various algorithms, and the high degree of fault tolerance. Thus it becomes the first choice of topological structure of parallel processing and computing systems. In this paper, lower bounds for the dilation, wirelength, and edge congestion of an embedding of a graph into a hypercube are proved. Two of these bounds are expressed in terms of the bisection width. Applying these results, the dilation and wirelength of embedding of certain complete multipartite graphs, folded hypercubes, wheels, and specific Cartesian products are computed.

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On g-extra conditional diagnosability of hierarchical cubic networks

Cited by 14 publications

References 28 publications

Component (edge) connectivity of pancake graphs

Component (edge) connectivity of pancake graphs

A general approach to deriving diagnosability results of interconnection networks*

Lower bounds for dilation, wirelength, and edge congestion of embedding graphs into hypercubes

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