A Network Troubleshooting System Using Augmented Reality Technology (ユビキタスコンピューティングシステム(UBI) Vol.2010-UBI-26) A Network Troubleshooting System Using Augmented Reality Technology

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Author(s)

Abstract

We envision that in the future, the users will be more involved in the management aspect of the network. This is due to the users are becoming more dependent on the network either for personal or business matters. However network management is a complicated task and still a closed domain affair by the network service providers. In this paper, we propose TIARA, a network troubleshooting system that utilizes the Augmented Reality technology. TIARA allows user to perform network troubleshooting seamlessly by using visualization of management information of network devices. TIARA architecture reduces the technology gap between the users and the complexity of network management. We measure the performance of TIARA and the results show that TIARA performs reasonably well in terms of the time taken to visualize the information.We envision that in the future, the users will be more involved in the management aspect of the network. This is due to the users are becoming more dependent on the network either for personal or business matters. However network management is a complicated task and still a closed domain affair by the network service providers. In this paper, we propose TIARA, a network troubleshooting system that utilizes the Augmented Reality technology. TIARA allows user to perform network troubleshooting seamlessly by using visualization of management information of network devices. TIARA architecture reduces the technology gap between the users and the complexity of network management. We measure the performance of TIARA and the results show that TIARA performs reasonably well in terms of the time taken to visualize the information.

Journal

  • 研究報告ユビキタスコンピューティングシステム(UBI)

    研究報告ユビキタスコンピューティングシステム(UBI) 2010-UBI-26(7), 1-6, 2010-05-21

    情報処理学会

References:  6

Codes

  • NII Article ID (NAID)
    110007995234
  • NII NACSIS-CAT ID (NCID)
    AA11838947
  • Text Lang
    ENG
  • Article Type
    Technical Report
  • ISSN
    09196072
  • NDL Article ID
    025051273
  • NDL Call No.
    YH247-911
  • Data Source
    CJP  NDL  NII-ELS  IPSJ 
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