Abstract: Random failures and targeted attacks may cause links or nodes in the network failure, which in turn can cause significant disruption to the availability of network services. Designing a network topology to provide acceptable levels of service in the face of these challenges can save both lives and money. Therefore, this paper proposes a heuristic algorithm based on iterative computing to optimize the network topology, which adds links to given graphs to improve the average efficiency function of the network and enhance network resilience. The algorithm is used in three kinds of complex networks to maximize the average efficiency of a network via adding a set of links. Then, non-improved and improved graphs are evaluated by applying random failure and centrality-based attacks to examine their resilience. The results show that compared with other optimization algorithms, the proposed heuristic algorithm yields the best network resilience against such attacks among the studied robustness metrics.

Key words: graph robustness, spectral graph theory, network resilience, random failures, targeted attacks, network topology

摘要： 由于复杂网络环境下的随机故障和恶意攻击可能引起网络中节点或者链路故障，进而对网络服务的可用性造成明显破坏，设计和构建应对网络失效的弹性网络拓扑可以延长网络寿命节约网络成本，因此，提出了一种基于迭代计算的启发式算法优化网络拓扑，对给定图添加链路改善网络的平均效率函数，提高网络弹性。将该算法用于3种复杂网络拓扑并且比较算法的效益。通过采用随机故障和基于中心性的攻击，测试和评估原始图和改善图的网络弹性。与图谱理论的一些弹性优化算法进行对比，仿真结果表明在所研究的弹性量化指标中，所提出的启发式算法可以优化网络拓扑，相比于其他的改进算法应对随机故障和中心性攻击更加具有弹性。

关键词: 图健壮性, 图谱, 网络弹性, 随机故障, 恶意攻击, 网络拓扑