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Fault tolerance assessment for hamming graphs based on r-restricted R-structure(substructure) fault pattern
Applied Mathematics and Computation ( IF 3.5 ) Pub Date : 2024-11-12 , DOI: 10.1016/j.amc.2024.129160
Yayu Yang, Mingzu Zhang, Jixiang Meng

The interconnection network between the storage system and the multi-core computing system is the bridge for communication of enormous amounts of data access and storage, which is the critical factor in affecting the performance of high-performance computing systems. By enforcing additional restrictions on the definition of R-structure and R-substructure connectivities to satisfy that each remaining vertex has not less than r neighbors, we can dynamically assess the cardinality of the separated component to meet the above conditions under structure faulty, thereby enhancing the evaluation of the fault tolerance and reliability of high-performance computing systems. Let R be a connected subgraph of a connected graph G. The r-restricted R-structure connectivity κr(G;R) (resp. r-restricted R-substructure connectivity κrs(G;R)) of G is the minimum cardinality of a set of subgraphs F={F1,F2,,Fm} such that Fi is isomorphic to R (resp. Fi is a connected subgraph of R) for 1im, and GF is disconnected with the minimum degree of each component being at least r. Note that κr(G;K1) reduces to r-restricted connectivity κr(G) (also called r-good neighbor connectivity). In this paper, we focus on κr(KLn;R) and κrs(KLn;R) for the L-ary n-dimensional hamming graph KLn, where R{K1,K1,1,KL1}. For 0rn3, n3 and L3, we determine the (L1)r-good neighbor connectivity of KLn, i.e., κ(L1)r(KLn)=(L1)(nr)Lr, and the (L1)r-good neighbor diagnosability of KLn under the PMC model and MM* model, i.e., t(L1)r(KLn)=[(L1)(nr)1]Lr1. And we also drive that κ(L1)r(KLn;K1,1)=κ(L1)rs(KLn;K1,1)=12(L1)Lr(nr) for 1rn3, n4. Moreover, we offer an upper bound of κ2(KLn;KL1) (resp. κ2s(KLn;KL1)) for n3, and establish that it is sharp for ternary n-cubes K3n. Specifically, κ2(K3n;K31)=κ2s(K3n;K31)=2(n1) for n3.

中文翻译:


基于 r 限制 R 结构(子结构)故障模式的汉明图容错评估



存储系统与多核计算系统之间的互连网络是海量数据访问和存储通信的桥梁,是影响高性能计算系统性能的关键因素。通过对 R 结构和 R 子结构连接性的定义施加额外的限制,以满足每个剩余的顶点具有不少于 r 个邻居,我们可以动态评估分离分量的基数以满足结构故障下的上述条件,从而增强对高性能计算系统的容错性和可靠性的评估。设 R 为连通图 G 的连通子图。r 受限的 R 结构连通性 κr(G;R) (resp. r 限制性 R 子结构连接 κrs(G;R)) 是一组子图 F={F1,F2,...,Fm} 的最小基数,使得 Fi 与 R 同构(或者 Fi 是 R 的连通子图)为 1≤i≤m,并且 G-F 断开连接,每个分量的最小度至少为 r。请注意,κr(G;K1) 减少到 r 限制连接 κr(G)(也称为 r 好邻居连接)。在本文中,我们重点介绍了 κr(KLn;R) 和 κrs(KLn;R) 的 L 元 n 维汉明图 KLn,其中 R∈{K1,K1,1,KL1}。对于 0≤r≤n-3、n≥3 和 L≥3,我们确定了 KLn 的 (L-1)r-好邻居连通性,即 κ(L-1)r(KLn)=(L-1)(n-r)Lr,以及 PMC 模型和 MM* 模型下 KLn 的 (L-1)r-好邻居可诊断性,即 t(L-1)r(KLn)=[(L-1)(n-r)--1]Lr-1。我们还驱动 κ(L−1)r(KLn;K1,1)=κ(L−1)rs(KLn;K1,1)=12(L-1)Lr(n-r) 为 1≤r≤n-3,n≥4。此外,我们提供了 κ2(KLn;KL1) (或 κ2s(KLn;KL1)) 对于 n≥3,并确定它对于三元 n 立方 K3n 是尖锐的。 具体来说,κ2(K3n;K31)=κ2s(K3n;K31)=2(n-1) 对于 n≥3。
更新日期:2024-11-12
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