Optimal tree packing for discretized live rate-adaptive streaming in CDN

Rate-adaptive streaming technologies, such as the Dynamic Adaptive Streaming over HTTP (DASH) standard, provides an efficient and easy solution to stream multimedia in a heterogenous context. However, it reinforces the streaming capacity problem in the core Content Delivery Network (CDN) infrastructure since delivering one video means delivering an aggregation of multiple representations. In particular, for live rate-adaptive streaming , a large set of non-divisible data streams need to be either delivered in whole, or not delivered at all. Previous theoretical models that deal with streaming capacity problems are based on elastic bit rates, and do not capture these emerging features faced by today’s CDNs. In this paper, we identify a new, discretized streaming model, for live rate-adaptive video delivery in CDNs. For this model we formulate a general optimization problem and show that it is NP-complete. Then we study two fundamental scenarios that occur in real CDNs. For each of these scenarios, we present a fast, easy to implement, and near-optimal algorithm with performance approximation ratios that are negligible for large networks. These are the first sets of results for the discretized streaming model, and have both practical and theoretical importance in a topic that has become critical.