Towards Improved DASH Adaptation in NDN: An Emulative Analysis

摘要

The Information-Centric Networking (ICN) paradigm is deemed to enable simpler and more efficient networking interaction by moving from a strict connection based relationship between client and server to an interest-based relationship between user and content. Hence, addressing shifts to content objects rather than any specific copy or location of the content. In order to achieve this new way of addressing the client uses the content name, which is propagated into the network. As a result, a higher efficiency is expected since ICN network nodes (e.g., routers) may reply to such requests using copies from their own caches, or different sources hosting a content object may be used in parallel. Thus, this concept promises better support for device mobility and implicit caching, and it provides inherent multicast support.However, the simplicity of this concept comes at a price. As established applications, such as adaptive bitrate video streaming, have been designed and optimized having a client-server networking environment in mind. In particular, the quality adaptation algorithms used by today's de-facto streaming standard Dynamic Adaptive Streaming over HTTP (DASH) uses bandwidth estimation techniques that are specifically designed for a client-server networking environment where all video segments are retrieved from the same host.This paper addresses issues related to adaptive video streaming in an ICN environment. It analyzes the video streaming behavior of state-of-the-art video quality adaptation algorithms such as PANDA and BOLA in emulated ICN environments. The analysis focuses on the impact ICN chunk-based throughput measurements and ICN caches have on quantitative measurements of Quality-of-Experience (QoE). The paper provides a detailed investigation of the chunk-based throughput estimation showing that it behaves fundamentally different due to ICN caching. Based on these results we provide extensions to existing adaptation algorithms (e.g., PANDA) that can significantly improve the QoE in ICN environments.