Abstract
With the development of communication technology and the explosive growth of video traffic brought by the rapid growth of mobile devices (such as smartphones and wearable devices), great business opportunities have been brought to video service providers. In this paper, we make full use of the cache and computing capacity of edge cloud. Considering the multi bitrate of video, we design the video caching and processing model that offers maximized profit to video service provider. Specifically, we model this problem as the 0-1 optimization problem and design the learning-based online upper confidence bound algorithm based on multi-arm bandit theory. This algorithm can design the corresponding cache and process strategy in real time according to the users' request to video. Furthermore, this strategy can maximize the profit of video provider and satisfy the service quality for users. Finally, experimental results show that our proposed video caching and processing scheme is superior to other schemes.
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