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arXiv 1701.04581cs.NIcs.SI
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基于动态复杂网络的数据通信网络建模与性能研究

Modeling and Performance Studies of Data Communication Networks using Dynamic Complex Networks

Suchi Kumari, Anurag Singh

摘要:

所有现有的现实世界的网络都在不断发展,因此,在这些扩大的网络中的交通动力学的研究是一项具有挑战性的任务。关键问题是优化网络结构,提高网络容量,避免业务拥塞。我们感兴趣的是采取用户的路线,使其最不拥挤的最佳网络容量。通过优化网络拓扑结构和改进路由选择方法可以提高网络容量。在此背景下,我们提出并设计了一个模型的时变数据通信网络(TVCN)的基础上流入链路的动态。新出现的节点倾向于与网络中最有影响力的节点连接。在本文中,影响被称为\textit{reputation},并适用于计算在任何节点的整体拥塞。具有最小介数中心度和最大信誉的用户路径被优先用于路由。Kelly的速率分配问题的优化公式被用来获得不同的用户在不同的时刻的最佳速率,它被发现,具有最低介数中心和最高信誉的用户的路径将总是给最大速率在稳定点。

英文摘要:

All the existing real world networks are evolving, hence, study of traffic dynamics in these enlarged networks is a challenging task. The critical issue is to optimize the network structure to improve network capacity and avoid traffic congestion. We are interested in taking user's routes such that it is least congested with optimal network capacity. 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 in-flowing links. Newly appeared node prefers to attach with most influential node present in the network. In this paper, influence is termed as \textit{reputation} and is applied for computing overall congestion at any node. User path with least betweenness centrality and most reputation is preferred for routing. 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 stable point.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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