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 dynamic...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.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos.60704045 and 60804012)the Fundamental Research Funds for the Central Universities (Grant No.09Lgpy57)
文摘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.
