Bitrate Adaptation-aware Cache Partitioning for Video Streaming over Information-Centric Networks

• Published in: 2018 IEEE 43rd Conference on Local Computer Networks (LCN) pp. 401 - 408
• Main Authors: Li, Wenjie, Oteafy, Sharief M.A., Fayed, Marwan, Hassanein, Hossam S.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2018
• Subjects: Adaptation models; Bandwidth; Bit rate; Dynamic Adaptive Streaming; In-network Caching; Information Centric Networks; Internet; Named Data Networking; Oscillators; Quality of experience; Streaming media
• DOI: 10.1109/LCN.2018.8638113

Recent studies suggest that performance gains for content delivery over Information-centric Networks (ICNs) may be negated by Dynamic Adaptive Streaming (DAS), the de facto method for retrieval of multimedia content. The bitrate adaptation mechanism that drives video streaming appears to clash with generic ICN caching techniques in ways that affect users' Quality of Experience (QoE). Cache performance diminishes as video consumers dynamically select content encoded at different bitrates. Motivated by preliminary evidence suggesting the merits of bitrate-based cache partitioning, we introduce a scheme to dissect the cache capacity of routers along a forwarding path according to dedicated bitrates. To facilitate this partitioning, we propose a guiding principle RippleCache, which stabilizes bandwidth fluctuation while achieving high cache utilization by safeguarding high-bitrate content on the edge and pushing low-bitrate content into the network core. We further propose a cache placement scheme, RippleFinder, to realize this RippleCache principle and highlight its impact on users' QoE by cache partitioning. The performance gains are reinforced by evaluations in NS-3. Measurements show RippleFinder can significantly reduce bitrate oscillation, while ensuring high video quality, indicating overall improvement to QoE.