QoE-Aware Proactive Caching of Scalable Videos Over Small Cell Networks

TL;DR

This paper proposes an optimal proactive caching strategy for scalable video streaming in small cell networks, significantly improving user QoE by considering channel diversity, video scalability, and cache constraints.

Contribution

It introduces the first formulation of SVC caching as a multiple-choice knapsack problem and develops a low-complexity dynamic programming algorithm for optimal cache allocation.

Findings

Caching at SBSs greatly improves average QoE.

The proposed strategy outperforms conventional caching policies.

Structural properties of cache allocation are revealed.

Abstract

The explosion of mobile video traffic imposes tremendous challenges on present cellular networks. To alleviate the pressure on backhaul links and to enhance the quality of experience (QoE) of video streaming service, small cell base stations (SBS) with caching ability are introduced to assist the content delivery. In this paper, we present the first study on the optimal caching strategy of scalable video coding (SVC) streaming in small cell networks with the consideration of channel diversity and video scalability. We formulate an integer programming problem to maximize the average SVC QoE under the constraint of cache size at each SBS. By establishing connections between QoE and caching state of each video, we simplify the proactive caching of SVC as a multiple-choice knapsack problem (MCKP), and propose a low-complexity algorithm using dynamic programming. Our proactive caching strategy reveals the structural properties of cache allocation to each video based on their popularity profiles. Simulation results manifest that the SBSs with caching ability can greatly improve the average QoE of SVC streaming service, and that our proposed caching strategy acquires significant performance gain compared with other conventional caching policies.