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Improving node connectivity by optimized dual tree-based effective node consolidation
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AI
DOI：10.1016/j.ress.2023.109747.png)
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Abstract
En 中文
As an effective way to defend against network failure, nodes or links in a network can be protected to ensure connectivity. The consolidation of critical nodes is a necessary strategy, especially when nodes are important infrastructure elements, such as in wireless environments. However, since the problem is NP-hard, even the optimal algorithm is of high computational complexity on small-scale graphs, which makes it difficult to handle large-scale networks in feasible time. Fortunately, we have found an effective pairwise node cut set (NCS)-tree search method to locate small NCSes. The critical nodes in these NCSes are then selected to construct the optimal dual tree, and to determine the near optimal set of consolidation nodes. Comparison results show that the serial version of the proposed algorithm achieves a remarkable acceleration ratio of more than 105 compared to the optimal algorithm, with only a minimal additional cost. In addition, the consolidation solution provides protection for over 99.9% of vulnerable node pairs in large-scale networks and can significantly outperform common heuristics. Moreover, the ready-to-parallelization algorithm has the potential to be further accelerated hundreds of times in full parallelization.
Keywords:
Node connectivity
Node cut set
Node consolidation
Dual tree
Large-scale network
Journal
R
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