Return to search

A System, Tools and Algorithms for Adaptive HTTP-live Streaming on Peer-to-peer Overlays

In recent years, adaptive HTTP streaming protocols have become the de facto standard in the industry for the distribution of live and video-on-demand content over the Internet. In this thesis, we solve the problem of distributing adaptive HTTP live video streams to a large number of viewers using peer-to-peer (P2P) overlays. We do so by assuming that our solution must deliver a level of quality of user experience which is the same as a CDN while trying to minimize the load on the content provider’s infrastructure. Besides that, in the design of our solution, we take into consideration the realities of the HTTP streaming protocols, such as the pull-based approach and adaptive bitrate switching. The result of this work is a system which we call SmoothCache that provides CDN-quality adaptive HTTP live streaming utilizing P2P algorithms. Our experiments on a real network of thousands of consumer machines show that, besides meeting the the CDN-quality constraints, SmoothCache is able to consistently deliver up to 96% savings towards the source of the stream in a single bitrate scenario and 94% in a multi-bitrate scenario. In addition, we have conducted a number of pilot deployments in the setting of large enterprises with the same system, albeit tailored to private networks. Results with thousands of real viewers show that our platform provides an average offloading of bottlenecks in the private network of 91.5%. These achievements were made possible by advancements in multiple research areas that are also presented in this thesis. Each one of the contributions is novel with respect to the state of the art and can be applied outside of the context of our application. However, in our system they serve the purposes described below. We built a component-based event-driven framework to facilitate the development of our live streaming application. The framework allows for running the same code both in simulation and in real deployment. In order to obtain scalability of simulations and accuracy, we designed a novel flow-based bandwidth emulation model. In order to deploy our application on real networks, we have developed a network library which has the novel feature of providing on-the-fly prioritization of transfers. The library is layered over the UDP protocol and supports NAT Traversal techniques. As part of this thesis, we have also improved on the state of the art of NAT Traversal techniques resulting in higher probability of direct connectivity between peers on the Internet. Because of the presence of NATs on the Internet, discovery of new peers and collection of statistics on the overlay through peer sampling is problematic. Therefore, we created a peer sampling service which is NAT-aware and provides one order of magnitude fresher samples than existing peer sampling protocols. Finally, we designed SmoothCache as a peer-assisted live streaming system based on a distributed caching abstraction. In SmoothCache, peers retrieve video fragments from the P2P overlay as quickly as possible or fall back to the source of the stream to keep the timeliness of the delivery. In order to produce savings, the caching system strives to fill up the local cache of the peers ahead of playback by prefetching content. Fragments are efficiently distributed by a self-organizing overlay network that takes into account many factors such as upload bandwidth capacity, connectivity constraints, performance history and the currently being watched bitrate. / <p>QC 20131122</p>

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-134351
Date January 2013
CreatorsRoverso, Roberto
PublisherKTH, Programvaruteknik och Datorsystem, SCS, Stockholm
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeDoctoral thesis, comprehensive summary, info:eu-repo/semantics/doctoralThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationTRITA-ICT-ECS AVH, 1653-6363 ; 13:18

Page generated in 0.0019 seconds