Towards a scalable design of video content distribution over the internet

We are witnessing a proliferation of video in the Internet; YouTube is the most bandwidth intensive service of today’s Internet. It accounts for 20 - 35% of the Internet traffic with 35 hours of videos uploaded every minute and more than 700 billion playbacks in 2010. Netflix, a web service that streams premium contents such as TV series, shows, and movies, consumes 30% of the network bandwidth in North America at peak time. Recently, leveraging the content distribution networks (CDNs), a new paradigm for video streaming on the Internet has emerged, namely, Adaptive HTTP Streaming (AHS). AHS has become the industry standard for video streaming over the Internet adopted by broadcast networks as well as VoD services such as YouTube, Netflix, Hulu, etc. In the 90’s and early 2000’s, Internet-based video streaming for high-bitrate video was challenging due to hardware limitations. In that era, to cover the hardware limitations, every software component of a video server needed to be carefully optimized to support the real-time guarantees for jitter-free video delivery. However, most of the software solutions have become less important with the remarkable hardware improvements over the past two decades. There is 100× speedup in CPU speeds; RAM capacity has increased by 1,000×; hard disk drive (HDD) capacity has grown by 10,000×. Today, CPU is no longer a bottleneck for video streaming. On the other hand, storage bandwidth and network bandwidth are still serious bottlenecks for large scale on-demand video streaming. In this dissertation, we aim at a scalable video content distribution system that addresses both storage bottleneck and network bottleneck. The first part of the dissertation pertains to the storage system on the server side: A multi-tiered storage system that exploits a flash memory solid-state drive (SSD) can meet the bandwidth needs in a much more cost- effective way than a traditional two-tier storage system. We first identify the challenges in architecting such a system given the performance quirks of flash-based SSDs, and the lim- itations of state-of-the-art multi-tiered storage systems for video streaming. Armed with the knowledge of these challenges, we show how to construct such a storage system and implement a real web server with multi-tiered storage, evaluate the system with AHS work- loads, and demonstrate significant performance gains while reducing the TCO. The second part of the dissertation pertains to the network system on the client side: Integrating peer- to-peer (P2P) technology with the client-server paradigm results in a much more scalable video content distribution system. AHS is a paradigm for client-driven video streaming; its philosophy matches well with that of P2P video streaming. An adaptation mechanism is the most important component of AHS that determines overall video streaming quality and user experience. We show a throughput-smoothing-based adaptation mechanism that is designed for a client-server architecture does not work well for a P2P architecture. We pro- vide a buffer-based adaptation mechanism, evaluate our solution with OMNeT++/INET simulator, and demonstrate significant performance gains.Ph.D

SATI: Scalable And Traffic efficient data dissemination Infrastructure for sensor-based distributed information services

When highly distributed data streaming services are fully realized, they will bring up new issues in delivering data streams to data consumers. First, data delivery scheme should be traffic efficient because the Internet can be easily inundated by a massive number of data streams. Also, the probing messages generated by many delivery schemes waste network resources. These problems are not easily solved by existing data delivery schemes because none of them consider the economic usage and measurement of network resource. This paper proposes SATI, an infrastructure that provides not only shared management and measurement of network information but also scalable and traffic efficient data delivery. Experimental results show that SATI is scalable and greatly reduces network traffic. I