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Performance Statistics

Last updated: 2022-09-28 14:28:48
    This document analyzes TRTC’s performance in terms of audio/video quality, latency, smoothness, stability, CPU usage, memory usage, battery consumption, heating, and other key indicators in tests under normal and poor network conditions and in different application scenarios (one-to-one, one-to-many, etc.).

    Performance Under Normal and Poor Network Conditions

    Scenario

    Video call, interactive live streaming, and audio call

    Parameter configuration

    Video call:
    Parameter
    Value
    Resolution
    368 x 640
    Bitrate
    400 Kbps
    Frame rate
    15
    
    Interactive live streaming:
    Parameter
    Value
    Resolution
    720 x 1280
    Bitrate
    1200 Kbps
    Frame rate
    15

    Poor network tolerance test

    The TRTC SDK was tested for its tolerance to different bad network conditions.
    
    
    explain
    For the metrics used to measure tolerance to poor network conditions, please see Appendix 1: Network Metrics.

    Audio MOS under poor network conditions

    TRTC can deliver relatively high-quality audio and low latency under poor network conditions. The table below lists TRTC’s performance and mean opinion score (MOS) under different poor network conditions.
    
    

    Client SDK Performance

    Tested devices

    Device
    Processor
    Memory
    Android device 1
    Qualcomm Snapdragon 835 - 8 cores
    6 GB
    Android device 2
    Kirin 980 - 8 cores
    8 GB
    iOS device 1
    Apple A8 - 2 cores
    1 GB
    iOS device 2
    Apple A13 - 6 cores
    4 GB

    Parameter configuration

    Parameter
    Value
    Resolution
    240 x 320
    Bitrate
    100 Kbps
    Frame rate
    15

    Test scheme

    Scenario: one-to-one, one-to-two, one-to-four, one-to-eight
    Duration: 30 min for each scenario
    Method: a Linux robot is used to simulate streaming in one-to-many scenarios. Each device is tested independently.

    Test result

    The TRTC SDK performs well in terms of CPU usage, memory usage, heating, and battery consumption. It uses a small amount of hardware resources but provides quality audio/video services.
    App CPU usage:
    
    
    
    App memory usage:
    
    
    
    System CPU usage
    
    
    
    System memory usage
    
    
    
    Battery drain after 30 min:
    
    
    
    Heat increase after 30 min:
    
    
    

    Appendix 1: Network Metrics

    Metric
    Description
    Example
    Loss
    Packet loss rate
    50%: for every 10 packets sent, 5 are lost.
    Delay
    Network delay
    200: Data packets are delivered by the network 200 ms after they are sent by the SDK.
    Jitter
    Network jitter
    300: Packet sending may be delayed 20 ms, 50 ms, 250 ms, 280 ms, or any value up to 300 ms. The average delay is 150 ms.
    
    

    Appendix 2: Performance Metrics Under Poor Network Conditions

    Performance Metric
    Description
    MOS
    An important measure of the audio quality of telecommunication systems. MOS is generated by Spirent Nomad using the POLQA standard. The higher the score, the higher the audio quality.
    End-to-end latency
    The time from when audio is captured at the sender end to when it is played back at the recipient end
    Poor network tolerance test
    Spirent Nomad is used to score the SDK under different poor network conditions using the POLQA standard. Foreman video sequences are used to send data, and frame intervals are monitored at the recipient end. Data is collected at 30 points over a course of 10 min or longer. If there are perceptible abnormalities of 3 min at more than 3 data points, or the SDK is unavailable for a relatively long period of time, the SDK is considered intolerant of the network conditions.
    
    notice
    Perceptual Objective Listening Quality Analysis (POLQA) is the ITU-T P.863 standard. It is a globally applicable standard used to score speech quality under different network conditions.
    

    Appendix 3: SDK Performance Indicators

    Indicator
    Description
    App CPU usage
    Android
    Non-normalized CPU usage of the app, which is the same as the results generated by Android Studio Profiler
    iOS
    CPU usage of the app, which is the same as the results generated by XcodePerfDog usage = Xcode usage / Number of cores
    System CPU usage
    Android
    Non-normalized CPU usage of the device, which is the same as the results generated by Android Studio Profiler
    iOS
    CPU usage of the device, which is the same as the results generated by XcodePerfDog usage = Xcode usage / number of cores
    Memory usage
    Android
    Proportional set size (PSS), which is the same as the results generated by Android Java API and Meminfo
    iOS
    Xcode memory, which is obtained via debug gauges
    Battery drain
    Decrease in battery percentage after 30 min (calculation starts the moment the battery percentage drops from 100% to 99%.)
    Heat increase
    Temperature is measured with a thermometer when the app is not launched. Then run the app for 30 min under different scenarios. Heat increase = Temperature after 30 min – Temperature when the app is not launched
    
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