A surge number of models has been proposed to model the Internet in the past decades.However,the issue on which models are better to model the Internet has still remained a problem.By analysing the evolving dynamics of the Internet,we suggest that at the autonomous system (AS) level,a suitable Internet model,should at least be heterogeneous and have a linearly growing mechanism.More importantly,we show that the roles of topological characteristics in evaluating and differentiating Internet models are apparently over-estimated from an engineering perspective.Also,we find that an assortative network is not necessarily more robust than a disassortative network and that a smaller average shortest path length does not necessarily mean a higher robustness,which is different from the previous observations.Our analytic results are helpful not only for the Internet,but also for other general complex networks.
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机译：University of St Andrews Reports Findings in Machine Learning (Accurate Forecasting of Emergency Department Arrivals With Internet Search Index and Machine Learning Models: Model Development and Performance Evaluation)
机译：Hefei University of Technology Reports Findings in Chaos Research (Effects of topological characteristics on rhythmic states of the Ddimensional Kuramoto model in complex networks)
机译：Evaluation of water resources conserved by forests in the Hani rice terraces system of Honghe County, Yunnan, China: an application of the fuzzy comprehensive evaluation model
