Methods for Improving the Efficiency of Information and Communication Networks

Shvedov, A. V.; Nazarov, Mirzohuseyn J.

doi:10.1109/emctech49634.2020.9261563

Cited by 12 publications

(1 citation statement)

References 3 publications

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“…In the real world, complex network systems have a wide distribution. As research progresses and knowledge of the internal framework principles of network systems is constantly updated, more and more network science theories are being applied to the study of complex networks, and many properties of complex network characteristics such as a scale-free, small world, community structure [ 1 , 2 , 3 ] are proposed, which lay a solid foundation for the systematic application of network science to bioscience, social opinion, transportation planning, communication [ 4 , 5 , 6 , 7 ]. At the same time, the rich network elements and complex system features found in real networks continue to contribute to the development of network science.…”

Section: Introductionmentioning

confidence: 99%

An Internet-Oriented Multilayer Network Model Characterization and Robustness Analysis Method

Zhang

Yang

et al. 2022

Entropy

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The Internet creates multidimensional and complex relationships in terms of the composition, application and mapping of social users. Most of the previous related research has focused on the single-layer topology of physical device networks but ignored the study of service access relationships and the social structure of users on the Internet. Here, we propose a composite framework to understand how the interaction between the physical devices network, business application network, and user role network affects the robustness of the entire Internet. In this paper, a multilayer network consisting of a physical device layer, business application layer and user role layer is constructed by collecting experimental network data. We characterize the disturbance process of the entire multilayer network when a physical entity device fails by designing nodal disturbance to investigate the interactions that exist between the different network layers. Meanwhile, we analyze the characteristics of the Internet-oriented multilayer network structure and propose a heuristic multilayer network topology generation algorithm based on the initial routing topology and networking pattern, which simulates the evolution process of multilayer network topology. To further analyze the robustness of this multilayer network model, we combined a total of six target node ranking indicators including random strategy, degree centrality, betweenness centrality, closeness centrality, clustering coefficient and network constraint coefficient, performed node deletion simulations in the experimental network, and analyzed the impact of component types and interactions on the robustness of the overall multilayer network based on the maximum component change in the network. These results provide new insights into the operational processes of the Internet from a multi-domain data fusion perspective, reflecting that the coupling relationships that exist between the different interaction layers are closely linked to the robustness of multilayer networks.

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