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online.py
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online.py
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''' Demo SDK for LiveStreaming
Author Dan Yang
Time 2018-10-15
For LiveStreaming Game'''
# import the env from pip
import LiveStreamingEnv.fixed_env as fixed_env
#import fixed_env
import LiveStreamingEnv.load_trace as load_trace
#import matplotlib.pyplot as plt
import time
import numpy as np
import tensorflow as tf
import ABR
# path setting
def test(user_id):
#TRAIN_TRACES = '/home/game/test_sim_traces/' #train trace path setting,
#video_size_file = '/home/game/video_size_' #video trace path setting,
#LogFile_Path = "/home/game/log/" #log file trace path setting,
TRAIN_TRACES = './network_trace/' #train trace path setting,
video_size_file = './video_trace/AsianCup_China_Uzbekistan/frame_trace_' #video trace path setting,
LogFile_Path = "./log/" #log file trace path setting,
# Debug Mode: if True, You can see the debug info in the logfile
# if False, no log ,but the training speed is high
DEBUG = False
# load the trace
all_cooked_time, all_cooked_bw, all_file_names = load_trace.load_trace(TRAIN_TRACES)
#random_seed
random_seed = 2
count = 0
video_count = 0
FPS = 25
frame_time_len = 0.04
reward_all_sum = 0
#init
#setting one:
# 1,all_cooked_time : timestamp
# 2,all_cooked_bw : throughput
# 3,all_cooked_rtt : rtt
# 4,agent_id : random_seed
# 5,logfile_path : logfile_path
# 6,VIDEO_SIZE_FILE : Video Size File Path
# 7,Debug Setting : Debug
net_env = fixed_env.Environment(all_cooked_time=all_cooked_time,
all_cooked_bw=all_cooked_bw,
random_seed=random_seed,
logfile_path=LogFile_Path,
VIDEO_SIZE_FILE=video_size_file,
Debug = DEBUG)
abr = ABR.Algorithm()
abr_init = abr.Initial()
BIT_RATE = [500.0,850.0,1200.0,1850.0] # kpbs
TARGET_BUFFER = [2.0,3.0] # seconds
# ABR setting
RESEVOIR = 0.5
CUSHION = 2
cnt = 0
# defalut setting
last_bit_rate = 0
bit_rate = 0
target_buffer = 0
# QOE setting
reward_frame = 0
reward_all = 0
SMOOTH_PENALTY= 0.02
REBUF_PENALTY = 1.5
LANTENCY_PENALTY = 0.005
# past_info setting
past_frame_num = 7500
S_time_interval = [0] * past_frame_num
S_send_data_size = [0] * past_frame_num
S_chunk_len = [0] * past_frame_num
S_rebuf = [0] * past_frame_num
S_buffer_size = [0] * past_frame_num
S_end_delay = [0] * past_frame_num
S_chunk_size = [0] * past_frame_num
S_play_time_len = [0] * past_frame_num
S_decision_flag = [0] * past_frame_num
S_buffer_flag = [0] * past_frame_num
S_cdn_flag = [0] * past_frame_num
# params setting
while True:
reward_frame = 0
# input the train steps
#if cnt > 5000:
#plt.ioff()
# break
#actions bit_rate target_buffer
# every steps to call the environment
# time : physical time
# time_interval : time duration in this step
# send_data_size : download frame data size in this step
# chunk_len : frame time len
# rebuf : rebuf time in this step
# buffer_size : current client buffer_size in this step
# rtt : current buffer in this step
# play_time_len : played time len in this step
# end_delay : end to end latency which means the (upload end timestamp - play end timestamp)
# decision_flag : Only in decision_flag is True ,you can choose the new actions, other time can't Becasuse the Gop is consist by the I frame and P frame. Only in I frame you can skip your frame
# buffer_flag : If the True which means the video is rebuffing , client buffer is rebuffing, no play the video
# cdn_flag : If the True cdn has no frame to get
# end_of_video : If the True ,which means the video is over.
time,time_interval, send_data_size, chunk_len,\
rebuf, buffer_size, play_time_len,end_delay,\
cdn_newest_id, download_id, cdn_has_frame, decision_flag,\
buffer_flag, cdn_flag, end_of_video = net_env.get_video_frame(bit_rate,target_buffer)
# S_info is sequential order
S_time_interval.pop(0)
S_send_data_size.pop(0)
S_chunk_len.pop(0)
S_buffer_size.pop(0)
S_rebuf.pop(0)
S_end_delay.pop(0)
S_play_time_len.pop(0)
S_decision_flag.pop(0)
S_buffer_flag.pop(0)
S_cdn_flag.pop(0)
S_time_interval.append(time_interval)
S_send_data_size.append(send_data_size)
S_chunk_len.append(chunk_len)
S_buffer_size.append(buffer_size)
S_rebuf.append(rebuf)
S_end_delay.append(end_delay)
S_play_time_len.append(play_time_len)
S_decision_flag.append(decision_flag)
S_buffer_flag.append(buffer_flag)
S_cdn_flag.append(cdn_flag)
# 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 - 4.3 * rebuf - 1.2 * end_delay
reward_frame += -1 * SMOOTH_PENALTY * (abs(BIT_RATE[bit_rate] - BIT_RATE[last_bit_rate]) / 1000)
# last_bit_rate
last_bit_rate = bit_rate
# -------------------------------------------Your Althgrithom -------------------------------------------
# which part is the althgrothm part ,the buffer based ,
# if the buffer is enough ,choose the high quality
# if the buffer is danger, choose the low quality
# if there is no rebuf ,choose the low target_buffer
bit_rate , target_buffer = abr.run(time,S_time_interval,S_send_data_size,S_chunk_len,S_rebuf,S_buffer_size, S_play_time_len,S_end_delay,S_decision_flag,S_buffer_flag,S_cdn_flag, end_of_video, cdn_newest_id, download_id,cdn_has_frame,abr_init)
# ------------------------------------------- End -------------------------------------------
if end_of_video:
print("video count", video_count, reward_all)
reward_all_sum += reward_all / 1000
video_count += 1
if video_count >= len(all_file_names):
break
cnt = 0
last_bit_rate = 0
reward_all = 0
bit_rate = 0
target_buffer = 0
S_time_interval = [0] * past_frame_num
S_send_data_size = [0] * past_frame_num
S_chunk_len = [0] * past_frame_num
S_rebuf = [0] * past_frame_num
S_buffer_size = [0] * past_frame_num
S_end_delay = [0] * past_frame_num
S_chunk_size = [0] * past_frame_num
S_play_time_len = [0] * past_frame_num
S_decision_flag = [0] * past_frame_num
S_buffer_flag = [0] * past_frame_num
S_cdn_flag = [0] * past_frame_num
reward_all += reward_frame
return reward_all_sum
a = test("aaa")
print(a)