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<p>Cycle composition networks (CCNs) are a class of topological structure, which not only contains <i>k</i>-ary <i>n</i>-cube and BC graph, but also includes the data center network CamCube and many other future networks. As the number of vertices in the network increases, successfully transmitting data between any two fault-free vertices becomes an important issue in network communication. This paper studies fault-tolerant path of CCNs, designs corresponding construction algorithms, proves the correctness of the algorithms, analyzes the performance of the algorithm, and conducts corresponding simulation experiments to verify the theoretical results. Numerous experiments have shown that the algorithm proposed in this paper has significant advantages over other algorithms in terms of average running time, and the difference between the average fault-free path length and the length obtained by the BFS algorithm is minimal.</p>

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An efficient algorithm to find a shorter fault-tolerant path in cycle composition networks

  • 期刊论文

  • 发表日期：

    2025年8月14日

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  • Yaqian Tang,
  • Bai Yin,
  • Baolei Cheng,
  • Yan Wang,
  • Jia Yu,
  • Jianxi Fan

摘要

Cycle composition networks (CCNs) are a class of topological structure, which not only contains k-ary n-cube and BC graph, but also includes the data center network CamCube and many other future networks. As the number of vertices in the network increases, successfully transmitting data between any two fault-free vertices becomes an important issue in network communication. This paper studies fault-tolerant path of CCNs, designs corresponding construction algorithms, proves the correctness of the algorithms, analyzes the performance of the algorithm, and conducts corresponding simulation experiments to verify the theoretical results. Numerous experiments have shown that the algorithm proposed in this paper has significant advantages over other algorithms in terms of average running time, and the difference between the average fault-free path length and the length obtained by the BFS algorithm is minimal.