Cache'n DASH

Abstract

HTTP-based video streaming services have been dominating the global IP traffic over the last few years. Caching of video content reduces the load on the content servers. In the case of Dynamic Adaptive Streaming over HTTP (DASH), for every video the server needs to host multiple representations of the same video file. These individual representations are further broken down into smaller segments. Hence, for each video the server needs to host thousands of segments out of which, the client downloads a subset of the segments. Also, depending on the network conditions, the adaptation scheme used at the client-end might request a different set of video segments (varying in bitrate) for the same video. The caching of DASH videos presents unique challenges. In order to optimize the cache hits and minimize the misses for DASH video streaming services we propose an Adaptation Aware Cache (AAC) framework to determine the segments that are to be prefetched and retained in the cache. In the current scheme, we use bandwidth estimates at the cache server and the knowledge of the rate adaptation scheme used by the client to estimate the next segment requests, thus improving the prefetching at the cache.