Since all the existing real world networks are evolving, the study of traffic dynamics is a challenging task. Avoidance of traffic congestion, system utility maximization and enhancement of network capacity are prominent issues. Network capacity may be improved either by optimizing network topology or enhancing in routing approach. In this context, we propose and design a model of the time-varying data communication networks (TVCN) based on the dynamics of inflowing links. Traffic congestion can be avoided by using a suitable centrality measure, especially betweenness and Eigen vector centralities. If the nodes coming in user’s route are most betweenness central, then that route will be highly congested. Eigen vector centrality is used to find the influence of a node on others. If a node is most influential, then it will be highly congested and considered as least reputed. For that reason, routes are chosen such that the sum of the centralities of the nodes coming in user’s route should be minimum. Furthermore, Kelly’s optimization formulation for a rate allocation problem is used for obtaining optimal rates of distinct users at different time instants and it is found that the user’s path with lowest betweenness centrality and highest reputation will always give maximum rate at the stable point.

中文翻译：

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时变网络建模及其最优路由策略

由于所有现有的现实世界网络都在不断发展，因此研究交通动态是一项具有挑战性的任务。避免交通拥堵、最大化系统效用和提高网络容量是突出问题。可以通过优化网络拓扑或增强路由方法来提高网络容量。在这种情况下，我们提出并设计了一个基于流入链路动态的时变数据通信网络（TVCN）模型。通过使用合适的中心性度量，尤其是介数和特征向量中心性，可以避免交通拥堵。如果进入用户路线的节点是最中间中心的，那么该路线将高度拥塞。特征向量中心性用于发现一个节点对其他节点的影响。如果一个节点是最有影响力的，那么它将高度拥挤并被认为是最不知名的。出于这个原因，选择路由使得进入用户路由的节点的中心性总和应该是最小的。此外，Kelly对速率分配问题的优化公式用于获得不同用户在不同时刻的最优速率，发现中介中心性最低、信誉最高的用户路径总是在稳定点给出最大速率。