# Rate-Distortion-Memory Trade-offs in Heterogeneous Caching Networks

## TL;DR

This paper explores the fundamental trade-offs between rate, distortion, and memory in heterogeneous caching networks, proposing new caching and delivery schemes that optimize video quality and load reduction in wireless edge caching.

## Contribution

It introduces a generalized framework for rate-distortion-memory trade-offs in heterogeneous caching networks with scalable video coding and proposes a decentralized lossy delivery scheme.

## Key findings

- Optimized caching and coded delivery strategies for scalable video in heterogeneous networks.
- Decentralized lossy cache-aided delivery scheme with preset distortion targets.
- Framework accounts for cache size, video popularity, and user quality preferences.

## Abstract

Caching at the wireless edge can be used to keep up with the increasing demand for high-definition wireless video streaming. By prefetching popular content into memory at wireless access points or end-user devices, requests can be served locally, relieving strain on expensive backhaul. In addition, using network coding allows the simultaneous serving of distinct cache misses via common coded multicast transmissions, resulting in significantly larger load reductions compared to those achieved with traditional delivery schemes. Most prior works simply treat video content as fixed-size files that users would like to fully download. This work is motivated by the fact that video can be coded in a scalable fashion and that the decoded video quality depends on the number of layers a user receives in sequence. Using a Gaussian source model, caching and coded delivery methods are designed to minimize the squared error distortion at end-user devices in a rate-limited caching network. The framework is very general and accounts for heterogeneous cache sizes, video popularities and user-file play-back qualities. As part of the solution, a new decentralized scheme for lossy cache-aided delivery subject to preset user distortion targets is proposed, which further generalizes prior literature to a setting with file heterogeneity.