ETSI Multi-Access Edge Computing for Dynamic Adaptive Streaming in Information Centric Networks

Using Information Centric Networks (ICNs) instead of IP networks will improve Quality of Experience (QoE) by enabling efficient and scalable Content Delivery Networks (CDNs). However, Information Centric based CDNs still face many challenges. The rate adaptation algorithms used in IP based CDNs can for instance lead to inaccurate estimations of Round-Trip Times (RTTs) in ICN settings. Furthermore, the network storage feature of ICN can introduce major oscillations in adaptive streaming. In this paper, we use the ETSI Multi Access Edge Computing (MEC) to tackle these issues. An overall system view (which includes the MEC server) and a novel rate adaptation algorithm are proposed. The proposed rate adaptation algorithm is validated with simulations and the results show that it significantly improves users' QoE due to higher accuracy and stability in rate estimation.