Bring the Content Closer to the End User

: In-Network Adaptation and Caching of Mobile Video

Abstract

The extensive growth in smartphone and tablet market has led to a continu-ous increase in mobile video traffic, which has urged mobile network operators (MNOs) to redesign their networks and search for cost-effective solutions to bring content closer to the end user. This enables support for more simultaneous video streams, while maintaining stringent delay bounds. However, with adaptive bit rate streaming (ABS) which provides multiple source video bit rates for a single video to meet the heterogeneity of user devices and network conditions, caching all rate variants significantly increases backhaul and storage requirements. There-fore, having cached the highest quality of video contents, this thesis proposes two methodologies to perform in-network video adaptation: (1) a perceptual quality-aware video adaptation scheme that encodes video sequences at a target bit rate;(2) a quality of experience (QoE)-aware video adaptation technique which drops packets from scalable video streams to produce lower bit-rate versions under QoE and delay constraints. These adaptation schemes then allocate resources to meet the delay limitation of the lower rate streams for power-efficient streaming over downlink OFDMA systems.
Alternatively, instead of transrating reactively cached contents, operators can implement intelligent caching in their networks. Predictable user demands can then be proactively served from content caches deployed at mobile gateways in the vicinity of users. Therefore, this thesis also evaluates the potential benefits from in-network caching of scalable videos and finds the trade-off between the potential savings from- and infrastructural costs of in-network caching.
In light of the increasing trend in virtualization of network functions, a cost-effective Caching-as-a-Service (CaaS) framework for virtual video caching in 5G mobile networks is proposed in this study. In order to evaluate the pros and cons of this CaaS approach, a virtual caching problem is formulated in order to maximize return on caching investment by finding the best trade-off between the cost of cache storage and bandwidth savings from caching video contents in the MNO’s cloud.

Date of Award	2017
Original language	English
Awarding Institution	King's College London
Supervisor	Abdol-Hamid Aghvami (Supervisor) & Panos Kosmas (Supervisor)