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__pycache__
final
network_trace
video_trace
ABR.py
README.md
__init__.py
a3c.py
demo.py
figure_1.png
online.py
submit.zip

README.md

Table of Contents

INFO

  • LiveStreamingDemo
  • For LiveStreaming Game SDK demo
  • Languages: python 2 or python 3
  • Document description:
    • demo.py --- An SDK to call the SIM, and you will fill your algorithm in it.
    • video_size_0 --- video trace (low_bitrate)
    • video_size_1 --- video trace (high_bitrate)
    • train_sim_trace --- network trace for training
    • test_sim_trace --- network trace for you test
    • ABR.py --- you need to copy your algorithm in demo file to this file and upload it in the website to get your score.
    • online.py --- ``the same as the file in the server to call you ABR.py, which helps you to debug your uploads.```

What you need to do ?

  • you should upload your algorithm in this area
        # -------------------------------------------Your Althgrithom -------------------------------------------
        # which part is the algorithm part ,the buffer based ,
        # if the buffer is enough, choose the high quality
        # if the buffer is in danger, choose the low  quality
        # if there is no rebuf , choose the low target_buffer
  
        if buffer_size < RESEVOIR:
            bit_rate = 0
        elif buffer_size >= RESEVOIR + CUSHION:
            bit_rate = 1
        rebuf_list = [i for i in S_rebuf if i > 0]
  
        if sum(rebuf_list) > sum(S_chunk_len):
            target_buffer = 0
        else:
            target_buffer = 1
  
        # ------------------------------------------- End  -------------------------------------------

Code structure

  • Init the env sim :
         net_env = env.Environment(all_cooked_time=all_cooked_time,       # physical time
                                  all_cooked_bw=all_cooked_bw,            # throughput
                                  all_cooked_rtt=all_cooked_rtt,          # rtt
                                 random_seed=random_seed,                 # random_seed
                                  logfile_path=LogFile_Path,              # log setting
                                  VIDEO_SIZE_FILE=video_size_file,        # video trace
                                  Debug = DEBUG)                          # Debug setting
  • Loop: The cnt control you train steps:
    if cnt > 50000:
          break;
  • every step you can get the observations from env:
        time, time_interval, send_data_size, chunk_len, rebuf, buffer_size, rtt, play_time_len,end_delay, decision_flag, buffer_flag,cdn_flag, end_of_video = net_env.get_video_frame(bit_rate,TARGET_BUFFER[target_buffer])
  • calculate the score
       # QOE setting 
       if not cdn_flag:
           reward_frame = frame_time_len * float(BIT_RATE[bit_rate]) / 1000  - REBUF_PENALTY * rebuf - LANTENCY_PENALTY  * end_delay
       else:
           reward_frame = -(REBUF_PENALTY * rebuf)
       if decision_flag or end_of_video:
           # reward formate = play_time * BIT_RATE - 1.5 * rebuf - 0.005 * end_delay - 0.02 smooth
           reward_frame -=  * SMOOTH_PENALTY * (abs(BIT_RATE[bit_rate] - BIT_RATE[last_bit_rate]) / 1000)
           

Trace Data setting

  • you will have two types of the trace, one is network trace, another is video trace

                 12 TRAIN_TRACES = './train_sim_traces/'   #train trace path setting,
                 13 video_size_file = './video_size_'      #video trace path setting,
    
  • Video trace: Video trace has N files.(N means the num of bitrate actions)

  • Video trace format

      |   Time(s)  | frame_data_size(b) |  is_I_flag |
      |------------|--------------------|------------|
      | 22.1131    | 321312             |   1        |  
    
  • Network trace Format:

      |Time(s)  | throughput(kpbs) | rtt(ms)|
      |---------|------------------|--------|
      |20.5     | 1.312            |   56   |
    

Draw settings

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

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
  • Log formate:

     real_time        :   physical time
     cdn_rebuf        :   cdn_rebuf time
     client_rebuf     :   client_rebuf time
     download_duration:   download time
     frame_size       :   download frame data size
     play_time_len    :   play the video time len in this download_duration
     download_id      :   download frame seq
     cnd_new_frame    :   the seq of the cdn newest frame
     client_buffer    :   the clinet buffer
     play_time        :   play time
     play_id          :   play frame seq
     latency          :   end to end latency
real_time 3.0476    cdn_rebuf0.0412	client_rebuf 0.000	download_duration 0.0000	frame_size 21569.0000	play_time_len 0.0412	download_id 76	cdn_newest_frame 76	client_buffer 2.9588	play_time 0.0412	play_id 1.0000	latency 2.9588	000
  • which 000 type means the cdn can't get the frame , you can see the cdn_rebuf = 0.0412, the download_id = cdn_newest_frame
real_time 0.8897	cdn_rebuf0.0278	client_rebuf 0.006	download_duration 0.0059	frame_size 14587.0000	play_time len 0.0000	download_id 23	cdn_newest_frame 22	client_buffer 0.9200	play_time 0.0000	play_id 0.0000	latency 0.9200	111
  • which 111 type means the buffering status , you can see the play_time_len = 0

real_time 4.8653	cdn_rebuf0.0000	client_rebuf 0.000	download_duration 0.0628	frame_size 36672.0000	play_time_len 0.0628	download_id 118	cdn_newest_frame 122	client_buffer 2.7584	play_time 1.9216	play_id 48.0000	latency 2.9184	222
  • which 222 type means the normal status, you can see the play_time_len = download_duration

skip events: skip_download_frame, play_frame, new_download_frame, ADD_frame428 357 528 100
  • which means that it happens the skip events, the player not download the next frame, but to download the next ADD_FRAME frame. to let the latency small.
ADD_Frame100
  • which means the player skip

About livestreaming player sim please click the http://www.aitrans.online

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