Design and implementation of periodic broadcast video servers

Periodic broadcast is an effective paradigm for large-scale dissemination of popular videos. In the periodic broadcast paradigm, a video file is logically partitioned into a number of segments. These segments are periodically broadcast (using mulitcast) on the server channels. A client tunes into one or more channels at proper times to download the video segments into the client disk buffer. The client typically switches channels to download subsequent segments while playing out one of the buffered segments. Periodic broadcast guarantees a bounded service delay, which is equal to the length of time to broadcast the first segment, regardless of the number of concurrent requests making it suitable for popular videos. Considerable research efforts have gone into designing many excellent periodic broadcast protocols in terms of minimizing the server network bandwidth and the client resources. However, there are only a few implementations of periodic broadcast protocols available. This is probably because little has been documented on how the memory and disk bandwidth resources of a periodic broadcast server should be allocated. In this thesis, we present a Generalized Periodic Broadcast Server (GPBS) model that supports any periodic broadcast protocol. Based on this model, we formulate and solve a new optimization problem whose solution provides insights into the server\u27s memory and disk resources allocation. We use our analysis to estimate (i) the effect of keeping some video segments in the server memory during the entire broadcast of the video, and (ii) the effect of data placement on disk in periodic broadcast servers. We also discuss our prototype implementation of GPBS. Our work facilitates future implementation and deployment of many existing periodic broadcast protocols

Scalable download protocols

Scalable on-demand content delivery systems, designed to effectively handle increasing request rates, typically use service aggregation or content replication techniques. Service aggregation relies on one-to-many communication techniques, such as multicast, to efficiently deliver content from a single sender to multiple receivers. With replication, multiple geographically distributed replicas of the service or content share the load of processing client requests and enable delivery from a nearby server.Previous scalable protocols for downloading large, popular files from a single server include batching and cyclic multicast. Analytic lower bounds developed in this thesis show that neither of these protocols consistently yields performance close to optimal. New hybrid protocols are proposed that achieve within 20% of the optimal delay in homogeneous systems, as well as within 25% of the optimal maximum client delay in all heterogeneous scenarios considered.In systems utilizing both service aggregation and replication, well-designed policies determining which replica serves each request must balance the objectives of achieving high locality of service, and high efficiency of service aggregation. By comparing classes of policies, using both analysis and simulations, this thesis shows that there are significant performance advantages in using current system state information (rather than only proximities and average loads) and in deferring selection decisions when possible. Most of these performance gains can be achieved using only “local” (rather than global) request information.Finally, this thesis proposes adaptations of already proposed peer-assisted download techniques to support a streaming (rather than download) service, enabling playback to begin well before the entire media file is received. These protocols split each file into pieces, which can be downloaded from multiple sources, including other clients downloading the same file. Using simulations, a candidate protocol is presented and evaluated. The protocol includes both a piece selection technique that effectively mediates the conflict between achieving high piece diversity and the in-order requirements of media file playback, as well as a simple on-line rule for deciding when playback can safely commence

Analysis of Routing Characteristics in the Multicast Infrastructure

As the multicast-capable part of the Internet continues to evolve, important questions to ask are whether the protocols are operating correctly, the topology is well connected, and the routes are stable. A critical step in being able to answer these questions is to monitor the traffic and network operation. In this paper, we analyze characteristics of the multicast infrastructure over the last three years using monitoring data collected from several key routers. Specifically, we focus on analyzing two characteristics of the infrastructure: size and stability. The size analysis focuses on counting the number of connected hosts and networks, and analyzing how the size of the infrastructure has changed over past three years. Second, the stability analysis focuses on examining persistence, prevalence, and visibility of routes across the topology. From our analyses, we identify a number of problems with multicast routing and their effect on the connectivity of certain multicast networks. Moreover, we offer insight into the evolution and future of multicast in the Internet. I

Analysis of Routing Characteristics in the Multicast Infrastructure Abstract — As the multicast-capable part of the Internet continues

to evolve, important questions to ask are whether the protocols are operating correctly, the topology is well connected, and the routes are stable. A critical step in being able to answer these questions is to monitor the traffic and network operation. In this paper, we analyze characteristics of the multicast infrastructure over the last three years using monitoring data collected from several key routers. Specifically, we focus on analyzing two characteristics of the infrastructure: size and stability. The size analysis focuses on counting the number of connected hosts and networks, and analyzing how the size of the infrastructure has changed over past three years. Second, the stability analysis focuses on examining persistence, prevalence, and visibility of routes across the topology. From our analyses, we identify a number of problems with multicast routing and their effect on the connectivity of certain multicast networks. Moreover, we offer insight into the evolution and future of multicast in the Internet. I