KANVAS: A Network Information Sharing Framework Based on Network Ontology Bonsai

Kanta Kuchii, Takao Kondo, Fumio Teraoka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Demands for acquiring Internet behavior are increasing for Internet-scale network understanding such as inter-AS path management and traffic engineering. Although there are several efforts to make Internet behavior public, most of the public information is not structured and it is hard for applications to use such information. This paper proposes a network information sharing framework called KANVAS. It defines a network ontology called Bonsai which models network structure from viewpoints of physical, logical, service, and operation network structures. Bonsai can express network virtualization technologies such as link aggregation (LAG), VLAN, L2 over L3 tunneling, and virtual routing and forwarding (VRF). Applications can access network information via useful API. As a first step of development of KANVAS and Bonsai, this paper describes network information sharing within a single domain focusing on failure localization and throughput monitoring as examples. Evaluation results on a PoC system show that the time for failure localization is short enough and a throughput monitoring tool can choose appropriate monitoring points.

Original languageEnglish
Title of host publicationAsian Internet Engineering Conference, AINTEC 2022
PublisherAssociation for Computing Machinery
Number of pages9
ISBN (Electronic)9781450399814
Publication statusPublished - 2022 Dec 19
Event17th Asian Internet Engineering Conference, AINTEC 2022 - Hiroshima, Japan
Duration: 2022 Dec 192022 Dec 21

Publication series

NameACM International Conference Proceeding Series


Conference17th Asian Internet Engineering Conference, AINTEC 2022


  • fault localization
  • network management
  • network ontology
  • traffic monitoring

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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