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KSII Transactions on Internet and Information Systems, 2021, 15(8), , pp.2764-2782
2021
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Autor(en) / Beteiligte
Titel
A City-Level Boundary Nodes Identification Algorithm Based on Bidirectional Approaching
Ist Teil von
  • KSII Transactions on Internet and Information Systems, 2021, 15(8), , pp.2764-2782
Ort / Verlag
KSII, the Korean Society for Internet Information
Erscheinungsjahr
2021
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
  • Existing city-level boundary nodes identification methods need to locate all IP addresses on the path to differentiate which IP is the boundary node. However, these methods are susceptible to time-delay, the accuracy of location information and other factors, and the resource consumption of locating all IPes is tremendous. To improve the recognition rate and reduce the locating cost, this paper proposes an algorithm for city-level boundary node identification based on bidirectional approaching. Different from the existing methods based on time-delay information and location results, the proposed algorithm uses topological analysis to construct a set of candidate boundary nodes and then identifies the boundary nodes. The proposed algorithm can identify the boundary of the target city network without high-precision location information and dramatically reduces resource consumption compared with the traditional algorithm. Meanwhile, it can label some errors in the existing IP address database. Based on 45,182,326 measurement results from Zhengzhou, Chengdu and Hangzhou in China and New York, Los Angeles and Dallas in the United States, the experimental results show that: The algorithm can accurately identify the city boundary nodes using only 20.33% location resources, and more than 80.29% of the boundary nodes can be mined with a precision of more than 70.73%. Keywords: Internet measurement, Network topology, Boundary node identification, Bidirectional approaching.
Sprache
Englisch
Identifikatoren
ISSN: 1976-7277
eISSN: 1976-7277
DOI: 10.3837/tiis.2021.08.004
Titel-ID: cdi_nrf_kci_oai_kci_go_kr_ARTI_9857081

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