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Scaling of average weighted shortest path and average receiving time on weighted hierarchical networks

机译:加权分级网络上平均加权最短路径和平均接收时间的缩放

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Recent work on the networks has focused on the weighted hierarchical networks that are significantly different from the un-weighted hierarchical networks. In this paper we study a family of weighted hierarchical networks which are recursively defined from an initial uncompleted graph, in which the weights of edges have been assigned to different values with certain scale. Firstly, we study analytically the average weighted shortest path (AWSP) on the weighted hierarchical networks. Using a recursive method, we determine explicitly the AWSP. The obtained rigorous solution shows that the networks grow unbounded but with the logarithm of the network size, while the weighted shortest paths stay bounded. Then, depending on a biased random walk, we research the mean first-passage time (MFPT) between a hub node and any peripheral node. Finally, we deduce the analytical expression of the average of MFPTs for a random walker originating from any node to first visit to a hub node, which is named as the average receiving time (ART). The obtained result shows that ART is bounded or grows sublinearly with the network order relating to the number of initial nodes and the weighted factor or grows quadratically with the iteration.
机译:网络上的最新工作集中在加权的分层网络上,该网络与未加权的分层网络明显不同。在本文中,我们研究了一系列加权层次网络,这些网络是从初始未完成图递归定义的,其中边的权重已按一定比例分配给不同的值。首先,我们分析研究加权分级网络上的平均加权最短路径(AWSP)。使用递归方法,我们显式确定AWSP。严格的解决方案表明,网络无限制地增长,但具有网络大小的对数,而加权的最短路径保持有界。然后,根据有偏向的随机游走,我们研究了集线器节点与任何外围节点之间的平均首次通过时间(MFPT)。最后,我们推导了从任意节点到首次访问集线器节点的随机步行者的MFPT平均值的解析表达式,称为平均接收时间(ART)。所获得的结果表明,ART随与初始节点数和加权因子有关的网络阶数有界或亚线性增长,或者随着迭代而呈二次增长。

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