On Mapping the Interconnections in Today’s Internet

Motamedi, Reza; Yeganeh, Bahador; Chandrasekaran, B.; Rejaie, Reza; Maggs, Bruce M.; Willinger, Walter

doi:10.1109/tnet.2019.2940369

Cited by 20 publications

(9 citation statements)

References 53 publications

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“…Although many AS-level Internet-topology models have been studied, the models based on deep structural decomposition still need to be seriously investigated because the exponential growth of the topological scale has become a critical obstacle in the analysis of the current Internet behavior [38,39]. Structural decomposition is a useful means to reduce the complexity of the problems.…”

Section: Discussionmentioning

confidence: 99%

Structural Decomposition Model for the Evolution of AS-Level Internet Topologies

Zhang

2020

IEEE Access

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Modeling Internet graphs at the autonomous-system (AS) level is helpful for recognizing and predicting the development trend of evolving Internet topology from a macro perspective. In contrast to the global statistical models such as the power-law distribution of node degrees, the structural decomposition models can more effectively represent the local connection. In this paper, we propose a structure-based model. Starting with the classification of links among the AS nodes, the proposed model partitions the core and periphery of Internet graphs into 16 atomic-level solid and dotted components. Additionally, the model captures the stable evolving features of these components based on the UCLA dataset that continuously explore Internet graphs over a long historic period from 2001 to 2015. Finally, according to the structure-based model, we design a new Internet-topology generator. Compared with the recently proposed generators, the advantages of our generator are as follows: (1) it accurately captures the structure decomposition property studied in this work, (2) it performs best on three statistical properties of the distance, assortativity coefficient, and maximum degree, and (3) it exhibits the best comprehensive performance in terms of runtime and multiple graph properties.

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Section: Discussionmentioning

confidence: 99%

Structural Decomposition Model for the Evolution of AS-Level Internet Topologies

Zhang

2020

IEEE Access

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“…Claffy et al 15 believed that in provider-customer connections, the provider side provides the address space. This experience was used in the methods proposed by Huffaker et al 16 , Pansiot et al 17 , Motamedi et al 18 , and others. Also, since it does not apply to all cases, other heuristics were supplemented to improve the inference accuracy.…”

Section: Related Workmentioning

confidence: 99%

Inferring router ownership based on the classification of intra- and inter-domain links

Liu¹,

Zhao²,

Guo³

2023

Sci Rep

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Research on router ownership inference is central to many Internet studies, such as network failure diagnosis, network boundary identification, network resilience assessment, and inter-domain congestion detection. The existing router ownership inference method bdrmapIT has relatively few constraints on routers at the end of traceroute paths, resulting in some inference errors. In this paper, a router ownership inference method based on the classification of intra- and inter-domain links is proposed. In this method, the differentiating Internet Protocol (IP) address vector distance feature, the autonomous system relationship feature of the IP link, and the fan-in and fan-out features are designed to support the discrimination of IP link types. The use of additional information derived from the link type enriches the basis for router ownership inference and improves the accuracy of the inference result. Experimental results show that the accuracy reaches 96.4% and 94.6% on the two verification sets, respectively, which is 3.2–11.2% better than the existing typical methods.

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“…Some large content providers, including American and Chinese technology firms that are likely to be identified as "gatekeepers" under the DMA, have pursued vertical integration strategies through the construction of private backbone networks, edge computing facilities, and owned content delivery networks (CDN) that improve their ability to expand and change their digital infrastructure to improve the performance and quality of their services Sermpezis, Nomikos, and Dimitropoulos, 2017;Motamedi et al, 2019).…”

Section: Literaturementioning

confidence: 99%

Internet Infrastructure and Competition in Digital Markets

Hanspach

2022

SSRN Journal

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On Mapping the Interconnections in Today’s Internet

Cited by 20 publications

References 53 publications

Structural Decomposition Model for the Evolution of AS-Level Internet Topologies

Structural Decomposition Model for the Evolution of AS-Level Internet Topologies

Inferring router ownership based on the classification of intra- and inter-domain links

Internet Infrastructure and Competition in Digital Markets

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