Figure 2.

Robustness of seven real-world complex weighted networks with real and randomized link weights. Real-world complex weighted networks was analyzed comparing the robustness (R) of real and randomized link weights. In this figure we show the robustness (R) comparing outcomes of the real-world network with the randomized version of the same system. In the randomized network weights are reshuffled and randomly reassigned over the links; in this manner the binary-topological structure is maintained. The filled box indicates the robustness of the real-world system and the empty box of the same color contour shows the robustness of the randomized version of the same system. (a) Links removal strategies. (b) Nodes removal strategies. Eff indicates the weighted system efficiency computed on the real-world networks; Eff_ran is the weighted efficiency computed on the real-world network after the weights reshuffle, i.e. the real link weights are randomly re-assigned over the network. LCC indicates the largest connected cluster in in the network; LCC_ran is the largest connected cluster measures computed on the real-world network after the randomization of the weights; TF is the total flow in the network, i.e. the sum of the all link weights; TF_ran is the total flow computed on the real-world networks after the randomization of link weights. For the links removal strategy TF is not plotted because the real and the randomized link weights return the same hierarchy of links removal and thus the same outcomes of system total flow decrease. The random removal (Rand) and the randomized link weights network counterparts (LCC_ran, EFF_ran and TF_ran) are the average of 10⁴ simulations.