How SVC enables Distributed Caching in MEC?

TL;DR

This paper explores how scalable video coding (SVC) can facilitate distributed caching in multi-access edge computing (MEC) to reduce latency and improve content delivery efficiency for ultra-HD videos.

Contribution

It proposes an architecture leveraging SVC for distributed caching in MEC, enabling dynamic load balancing and latency reduction through layered video storage.

Findings

Distributed caching with SVC improves offloading probability.

Layered video storage balances latency and storage resources.

SVC-based caching adapts to network dynamics effectively.

Abstract

With an ever increasing demand for the delivery of internet video service, the service providers are facing a huge challenge to deliver ultra-HD (2k/4k) video at sub-second latency. The multi-access edge computing (MEC) platform actually helps in achieving this objective by caching popular contents at the edge of cellular network. This not only reduces the delivery latency, but also the load and the cost of the backhaul links. However, MEC platforms are afflicted by constrained resources in terms of storage and processing capabilities; and centralized caching of contents may nullify the advantage of reduced latency by lowering the offloading probability. Distributed caching at the edge not only improves the offloading probability, but also dynamically adjusts the load distribution among the MEC servers. In this article, we propose an architecture for deployment of MEC platforms by exploiting the characteristics of a scalable video encoding technique. The layered video coding techniques, such as the scalable video coding (SVC), is used by the content providers to adjust to the network dynamics, by dynamically dropping packets in order to reduce latency. We show how an SVC video easily lends itself to distributed caching at the edge. Then we investigate the latency-storage trade-off by storing the video layers at different parts of the access networks.