Cache-Version Selection and Content Placement for Adaptive Video Streaming in Wireless Edge Networks

TL;DR

This paper addresses the complex problem of optimizing content placement and cache-version selection for adaptive video streaming in wireless edge networks, proposing distributed algorithms that improve network utility and outperform heuristics.

Contribution

It introduces practical distributed algorithms for joint cache-version selection and content placement, with proven optimality and superior simulation performance.

Findings

Algorithms outperform baseline heuristics in simulations

Distributed approach effectively manages diverse user and network conditions

Proven optimality of the proposed algorithms

Abstract

Wireless edge networks are promising to provide better video streaming services to mobile users by provisioning computing and storage resources at the edge of wireless network. However, due to the diversity of user interests, user devices, video versions or resolutions, cache sizes, network conditions, etc., it is challenging to decide where to place the video contents, and which cache and video version a mobile user device should select. In this paper, we study the joint optimization of cache-version selection and content placement for adaptive video streaming in wireless edge networks. We propose practical distributed algorithms that operate at each user device and each network cache to maximize the overall network utility. In addition to proving the optimality of our algorithms, we implement our algorithms as well as several baseline algorithms on ndnSIM, an ns-3 based Named Data Networking simulator. Simulation evaluations demonstrate that our algorithms significantly outperform conventional heuristic solutions.