This repository contains the simulator code being used for ACM Multimedia 2019 Live Video Streaming. The simulator is a frame-level DASH video streaming simulator with a pluggable client module for bitrate control and latency control.

The simulator contains the following files:

• online.py : An SDK to call the SIM and ABR
• ABR.py : your ABR algorithm
• fixed_env.py : SIM code simulates live streaming player download, play, card, skip frame, etc
• load_trace.py : load trace to memory

The folder dataset contains the network traces and video traces. Please see the README.md file in the dataset directory for decsription of the dataset.

The simulator simulates a live video player，including downloading and playback of video frames. It reads as inputs:

1. A video trace, which contains the size of each video frame in a video file.
2. A network trace, which contains the network throughput at each time instance.
3. The bitrate control and latency control algorithm provided by participant.

The simulator output the following:

To run the simulator, you execute

python online.py

The given default code should produce something like the following:

video count 0 1182.2642188716964
video count 1 1377.7223845567382
video count 2 2205.3576390914172
video count 3 1563.6229626338486
video count 4 1005.8552370641194
video count 5 1730.894881578582
video count 6 1742.591282427159
video count 7 1742.9341512235237
video count 8 -1160.3554885566875
video count 9 754.6778329758246
video count 10 2604.537383217133
video count 11 1526.3693699344235
video count 12 1738.4296243574768
video count 13 1632.1525894295157
video count 14 103.31676372570564
video count 15 -134.73628719562478
video count 16 1503.0123339929692
video count 17 697.5516669070091
video count 18 1376.166009667083
video count 19 -749.3520074196668
22.44301254848225

• Setting

  • video trace setting:

             13 video_size_file = './video_size_'      #video trace path setting,
    

  • network trace setting:

             12 TRAIN_TRACES = './train_sim_traces/'   #train trace path setting, 
    

  • log setting

    • the log is used to debug the code. you can set you log file path:

           14 LogFile_Path = "./log/"                #log file trace path setting, 
      

    • if you are debugging your code, you can let the DEBUG = True.

    • if you are trainning your model, consider the I/O, advise you let the DEBUG = False

  • plot setting

    • if you want to Debug the code, the Draw = True, the image will let you know all kinds of indicators
    • 

       if DRAW:
           ax = fig.add_subplot(311)
           plt.ylabel("BIT_RATE")
           plt.ylim(300,1000)
           plt.plot(id_list,bit_rate_record,'-r')
    
           ax = fig.add_subplot(312)
           plt.ylabel("Buffer_size")
           plt.ylim(0,7)
           plt.plot(id_list,buffer_record,'-b')
    
           ax = fig.add_subplot(313)
           plt.ylabel("throughput")
           plt.ylim(0,2500)
           plt.plot(id_list,throughput_record,'-g')
    
           plt.draw()
           plt.pause(0.01)

• The participant should submit your ABR algorithm.
• The code must obey the demo sample.

• for detail info, Please vist the submit.

• for detail info, Please vist the Dataset.