  Experience of live video streaming can be improved if future available
bandwidth can be predicted more accurately at the video uploader side. Thus
follows a natural question which is how to make predictions both easily and
precisely in an ever-changing network. Researchers have developed many
prediction algorithms in the literature, from where a simple algorithm,
Arithmetic Mean (AM), stands out. Based on that, we are purposing a new method
called Empirical Conditional Method (ECM) based on a Markov model, hoping to
utilize more information in the past data to get a more accurate prediction
without loss of practicality.
  Through simulations, we found that our ECM algorithm performs better than the
commonly used AM one, in the sense of reducing the loss by about 10% compared
with AM. Besides, ECM also has a higher utilization rate of available
bandwidth, which means ECM can send more data out while not having a higher
loss rate or delay, especially under a low FPS setting. ECM can be more helpful
for those who have relatively limited networks to reach a more considerable
balance between frame loss rate and video quality hence improving the quality
of experience.
