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    CampusInsight – Campus Network Analyzer

    The CampusInsight is a campus network analyzer developed by Huawei. It uses big data analytics technologies to provide excellent network service experience by analyzing data of each user at each moment.
     
    The CampusInsight uses the Telemetry technology to dynamically capture fault data in seconds, perceiving the full-journey experience for each user. It proactively identifies four types of network problems, helping administrators quickly demarcate faults and eliminate risks and build excellent network service experience.

    Specifications

    Features Descriptions
    Multi-dimensional network status visualization and user experience awareness throughout the journey
    • Allows users to view multi-dimensional data statistics views based on different levels and regions.
    • Allows users to import topology views and plan AP locations to intuitively view fault location distribution.
    • Allows users to view the full-journey experience, including who, when, which AP to connect, experience, and issues.
    • Allows users to draw device profiles for APs and view the AP health status.
    • Traces the network access process of a client, including detailed protocol information at the association, authentication (supporting only the Dot1x authentication mode), and DHCP phases. The protocol information includes the interaction result and time consumed. If the interaction fails, the failure causes are also displayed.
    • Correlatively analyzes poor-experience clients. When experience of a client deteriorates, CampusInsight identifies quantified correlation KPIs based on the KPI similarity analysis algorithm, which effectively improves the accuracy of root cause identification. 
    Automatic identification and proactive prediction of network issues
    • Supports automatic identification of four types of network issues based on Big Data analysis and machine learning algorithms: connectivity, air interface performance, roaming, and device issues. The issues include authentication failure, weak-signal coverage, dual band capable client prefers 2.4G, and PoE power supply failure.
    • Supports learning and dynamic baseline drawing on network behavior to predict the change trend and detect exceptions through data comparison.
    Intelligent demarcation and root cause analysis of network issues
    • Supports issue distribution views, allowing users to view number of issues on different devices and number of affected clients. This helps users quickly focus on the devices where and time range when many issues occur. 
    • Supports issue impact analysis views, allowing users to filter impact factors from multiple dimensions and drill down layer by layer to quickly locate the issue root cause.
    • Analyzes the root causes and provides rectification suggestions to assist quick issue closure. 

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  • 达索系统3D体验高峰论坛暨广州智能制造大会召开 2019-05-18
  • 行摄最美乡村丹巴“美人谷”文章中国国家地理网 2019-05-18
  • 国宝级黄腹角雉住进三清山 2019-05-07
  • 新疆旅游推介会亮相北京 2019-05-07
  • 办过周永康、孙政才、令计划案的检法机关,拟双双换帅 2019-05-05
  • 中船重工总经理孙波涉嫌严重违纪违法接受中央纪委国家监委审查调查 2019-05-05
  • 人民网评:当好马克思主义的忠诚信奉者、坚定实践者 2019-05-04
  • 江苏泰兴长江边倾倒污泥“变本加厉” 2019-05-04
  • 内乱困扰西班牙 C罗亟须正名 2019-04-29
  • 一个企业里的劳动力,有可能被叫做职工,意指按职责做事的人,也可能被叫做劳工,意指按劳动力做事的人。不同的称呼,体现了不同的企业性质与追求。懂这点,你才明白这“意 2019-04-02
  • 全论坛的人都跟你一样不会算8421,把自己的祖宗十八代都算没了?[大笑] 2019-04-02
  • 国务院部署实施蓝天保卫战三年计划 2019-03-28
  • 陈小林的专栏作者中国国家地理网 2019-03-28
  • Time at old streets - Chongqing News - CQNEWS 2019-03-23
  • 人民网春季糖酒会专访双汇发展副总裁杜俊甫 2019-03-23
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