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iMaster NCE-CampusInsight

El analizador de redes de campus CampusInsight obtiene las métricas de la experiencia del usuario en segundos a través de telemetría. Con CampusInsight se visualiza la experiencia completa de cada usuario en la red Wi-Fi en tiempo real. Si se produce un fallo, el sistema permite rastrear y evaluar los datos del usuario para determinar dónde se ha producido.

CampusInsight analiza y recopila datos de acuerdo a través de algoritmos de IA y Big Data para identificar los cuatros tipos de errores comunes (conectividad, rendimiento de la interfaz de aire, roaming y fallos en el dispositivo) en la O&M de una red Wi-Fi. Además, CampusInsight analiza las causas raíz y ofrece sugerencias para solucionar para problemas individuales y colectivos. A través de un servicio proactivo de O&M se reducen las quejas de los usuarios de redes de campus y el OPEX de la red.

Huawei

Especificaciones

CampusInsight provides two editions: basic and advanced. The basic edition provides the following functions.


Feature Description
Multi-dimensional network status visualization and client experience awareness throughout the journey
  • Views multi-dimensional data statistics based on hierarchical regions.
  • Imports topologies and plans AP locations to intuitively view fault location distribution.
  • Views full-journey client experience, including who, when, and which AP is connected.
  • Supports device profiles and allows users to view the health status of switches and APs.
  • Traces the network access process of a client, including detailed protocol information at the association (not supported for wired clients), authentication (supporting only the Dot1x authentication mode), and DHCP phases. The protocol information includes the interaction result and time consumed. The issue locating time is reduced from hours to minutes.
  • Supports correlative analysis for poor-experience clients. When the 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, and non-5G preferred access issues.
  • Learns network behavior features and draws dynamic baselines to identify exceptions in an early stage of network quality deterioration.
  • Intelligently analyzes data reported at the second level and establishes an experience evaluation system from multiple dimensions. CampusInsight evaluates and ranks regions based on indicator weights, driving continuous improvement from poor experience to good experience and gradually improving the network quality. You can view the dynamic baseline comparison between the local region and other regions for each indicator. CampusInsight provides a radar chart of associated root cause indicators, enabling in-depth root cause analysis.
Intelligent demarcation and root cause analysis of network issues
  • Supports the issue distribution view, allowing users to view the number of issues on different devices and the number of affected clients. This helps users quickly focus on the devices and time ranges with more issues.
  • Supports the issue impact analysis view, allowing users to quickly demarcate issues through multi-dimensional association analysis and drill down layer by layer to determine the issue root cause.
  • Provides a site-based integrated topology of wired and wireless convergence. Through intelligent group issue pattern identification, you can visually and quickly demarcate issue points.
  • Analyzes the root causes and provides rectification suggestions to assist quick issue closure.

In addition to the preceding basic functions, the advanced package also provides the following value-added functions.


Feature Description
Audio and video service analysis Detects the setup and teardown of audio and video sessions in real time, automatically analyzes the quality of the audio and video streams using the eMDI and awareness technologies and displays session information, uplink and downlink poor-quality durations, and MOS values of the initiator and responder of audio and video calls.
Constraints:
  • This feature is supported only for audio and video applications that use non-encrypted SIP signaling and are carried by the RTP in the IPv4 scenario, for example, Huawei Video Phone 8950.
  • Audio and video service analysis is supported for switches, and audio service analysis is supported for APs.
Switches of V200R013C00 or a later version and APs of V200R010C00 or a later version are supported.

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