Evaluation and Optimization of Complex Network Resilience against Attacks

With the current communication network failures intensifying, they have characteristics of complexity and adaptability. This is no longer possible that networks can completely resist all kinds of network attacks. Targeted attacks and random failures may cause link or node removal, 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 prolong the network lifetime. In this paper, an iteration algorithm called average efficiency improved (AE-improved) algorithm is presented to improve the given robustness functions. The algorithm improves the topology resilience of three complex networks by adding a set of links to maximize the average efficiency of a network. 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 AE-improved algorithm we proposed yields the best network resilience against such attacks among the studied robustness metrics.