Analyzing Caching Benefits for YouTube Traffic in Edge Networks - A Measurement-Based Evaluation

Recent studies observed video download platforms which contribute a large share to the overall traffic mix in today's operator networks. Traffic related to video downloads has reached a level where operators, network equipment vendors, and standardization organizations such as the IETF start to explore methods in order to reduce the traffic load in the network. Success or failure of these techniques depend on caching potentials of the target applications' traffic patterns. Our work aims at providing detailed insight into caching potentials of one of the leading video serving platforms: YouTube. We monitored interactions of users of a large operator network with the YouTube video distribution infrastructure for the time period of one month. From these traffic observations, we examine parameters that are relevant to the operation and effectiveness of an in-network cache deployed in an edge-network. Furthermore, we use our monitoring data as input for a simulation and determine the caching benefits that could have been observed if caching had been deployed.