Cloud-assisted multimedia content delivery

Abstract

Cloud computing, which is among the trendiest computing paradigms in recent years, is believed to be most suitable for supporting network-centric applications by providing elastic amounts of bandwidth for accessing a wide range of resources on the y. In particular, geo-distributed cloud systems are widely in construction nowadays. They span multiple data centers at different geographical locations, thus offering many advantages to large-scale multimedia applications because of the abundance of on-demand storage/bandwidth capacities and their geographical proximity to different groups of users. In this thesis, we investigate the common fundamental challenges in how to efficiently leverage the power of cloud resources to facilitate multimedia content delivery in various modern real world applications, from different perspectives. First, from the perspective of application providers, we propose tractable procedures for both model analysis and system designs of supporting representative large scale multimedia applications in a cloud system, i.e., VoD streaming applications and social media applications, respectively. We further verify the effectiveness of these algorithms and the feasibility of their deployment under dynamic realistic settings in real-life cloud systems. Second, from the perspective of end users, we target our focus at mobile users. The rapidly increasing power of personal mobile devices, dwarfing even high-end devices, is providing much richer contents and social interactions to users on the move, and many more challenging applications are on the horizon. We explore the tough challenges of how to effectively exploit cloud resources to facilitate mobile services by introducing two cloud-assisted mobile systems (i.e., CloudMoV and vSky-Conf), and explain in details their design philosophies and implementation. Finally, from the perspective of the cloud providers, we realize existing data center networks lack the flexibility to support many core services, given our hands-on experiences from working with public cloud systems. One of the specific problem is, “bulk data transfers across geo-distributed datacenters". After formulating a novel and well-formed optimization model for treating the data migration problem, we design and implement a Delay Tolerant Migration (DTM) system based on the Beacon platform and standard OpenFlow APIs. The system realizes a reliable Datacenter to Datacenter (D2D) network by applying the software defined networking (SDN) paradigm. Real-world experiments under realistic network traffic demonstrate the efficiency of the design.