The Edge Connectivity of Expanded k-Ary n-Cubes

Author:

Wang Shiying1ORCID,Wang Mujiangshan2

Affiliation:

1. School of Mathematics and Information Science, Henan Normal University, Xinxiang, Henan 453007, China

2. School of Electrical Engineering and Computer Science, The University of Newcastle NSW 2308, Australia

Abstract

Mass data processing and complex problem solving have higher and higher demands for performance of multiprocessor systems. Many multiprocessor systems have interconnection networks as underlying topologies. The interconnection network determines the performance of a multiprocessor system. The network is usually represented by a graph where nodes (vertices) represent processors and links (edges) represent communication links between processors. For the network G, two vertices u and v of G are said to be connected if there is a (u,v)-path in G. If G has exactly one component, then G is connected; otherwise G is disconnected. In the system where the processors and their communication links to each other are likely to fail, it is important to consider the fault tolerance of the network. For a connected network G=(V,E), its inverse problem is that G-F is disconnected, where FV or FE. The connectivity or edge connectivity is the minimum number of F. Connectivity plays an important role in measuring the fault tolerance of the network. As a topology structure of interconnection networks, the expanded k-ary n-cube XQnk has many good properties. In this paper, we prove that (1) XQnk is super edge-connected (n3); (2) the restricted edge connectivity of XQnk is 8n-2 (n3); (3) XQnk is super restricted edge-connected (n3).

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Modeling and Simulation

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Reliability of augmented k-ary n-cubes under the extra connectivity condition;The Journal of Supercomputing;2023-03-28

2. Connectivity and Nature Diagnosability of Leaf-Sort Graphs;Journal of Interconnection Networks;2020-09

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