• Matlab
  • Simulink
  • NS3
  • OMNET++
  • NS2

Video Aware Scheduling and Caching in Radio Network

In this paper, we introduce distributed caching of videos at the base stations of the Radio Access Network (RAN) to significantly improve the video capacity and user experience of mobile networks. To ensure effectiveness of the massively distributed but relatively small-sized RAN caches, unlike Internet content delivery networks (CDNs) that can store millions of videos in a relatively few large-sized caches, we propose RAN-aware reactive and proactive caching policies that utilize User Preference Profiles (UPPs) of active users in a cell. Furthermore, we propose video-aware backhaul and wireless channel scheduling techniques that, in conjunction with edge caching, ensure maximizing the number of concurrent video sessions that can be supported by the end-to-end network while satisfying their initial delay requirements and minimize stalling.

To evaluate our proposed techniques, we developed a statistical simulation framework using MATLAB and performed extensive simulations under various cache sizes, video popularity and UPP distributions, user dynamics, and wireless channel conditions. Our simulation results show that RAN caches using UPP-based caching policies, together with video-aware backhaul scheduling, can improve capacity by 300% compared to having no RAN caches, and by more than 50% compared to RAN caches using conventional caching policies. The results also demonstrate that using UPP-based RAN caches can significantly improve the probability that video requests experience low initial delays. In networks where the wireless channel bandwidth may be constrained, application of our video-aware wireless channel scheduler results in significantly (up to 250%) higher video capacity with very low stalling probability.

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