论文标题
光谱启发式方法适用于顶点可靠性
Spectral Heuristics Applied to Vertex Reliability
论文作者
论文摘要
网络的可操作性涉及其保持运营的能力，尽管其链接或设备可能会发生故障。可以通过图对网络进行建模，以评估和增加此操作性。它的顶点和边缘分别与用户设备及其连接相对应。在本文中，考虑到仅在网络设备中发生故障的情况下，解决图表中的拓扑变化会导致相关网络的可操作性更大。更具体地说，我们提出了两种光谱启发式方法，以通过单个边缘插入来提高图形的顶点可靠性。这些启发式方法的性能以及通常在文献中发现的其他启发式方法，通过使用模型Erdos-renyi，Barabasi-Albert和Watts-Strogatz产生的22000次订单的计算实验进行了评估。从实验中，可以通过分析和应用统计检验观察到，其中一种光谱启发式方法在与其他测试有关的情况下表现出了较高的性能。
The operability of a network concerns its ability to remain operational, despite possible failures in its links or equipment. One may model the network through a graph to evaluate and increase this operability. Its vertices and edges correspond to the users equipment and their connections, respectively. In this article, the problem addressed is identifying the topological change in the graph that leads to a greater increase in the operability of the associated network, considering the case in which failure occurs in the network equipment only. More specifically, we propose two spectral heuristics to improve the vertex reliability in graphs through a single edge insertion. The performance these heuristics and others that are usually found in the literature are evaluated by computational experiments with 22000 graphs of orders 10 up to 20, generated using the Models Erdos-Renyi, Barabasi-Albert, and Watts-Strogatz. From the experiments, it can be observed through analysis and application of statistical test, that one of the spectral heuristics presented a superior performance in relation to the others.
