11,934 research outputs found
Exploiting Traffic Balancing and Multicast Efficiency in Distributed Video-on-Demand Architectures
Distributed Video-on-Demand (DVoD) systems are proposed as a
solution to the limited streaming capacity and null scalability of centralized
systems. In a previous work, we proposed a fully distributed large-scale VoD
architecture, called Double P-Tree, which has shown itself to be a good approach
to the design of flexible and scalable DVoD systems. In this paper, we
present relevant design aspects related to video mapping and traffic balancing in
order to improve Double P-Tree architecture performance. Our simulation results
demonstrate that these techniques yield a more efficient system and considerably
increase its streaming capacity. The results also show the crucial importance
of topology connectivity in improving multicasting performance in
DVoD systems. Finally, a comparison among several DVoD architectures was
performed using simulation, and the results show that the Double P-Tree architecture
incorporating mapping and load balancing policies outperforms similar
DVoD architectures.This work was supported by the MCyT-Spain under contract TIC 2001-2592 and partially supported by the Generalitat de Catalunya- Grup de Recerca Consolidat 2001SGR-00218
Modeling and Evaluation of Multisource Streaming Strategies in P2P VoD Systems
In recent years, multimedia content distribution has largely been moved to the Internet, inducing broadcasters, operators and service providers to upgrade with large expenses their infrastructures. In this context, streaming solutions that rely on user devices such as set-top boxes (STBs) to offload dedicated streaming servers are particularly appropriate. In these systems, contents are usually replicated and scattered over the network established by STBs placed at users' home, and the video-on-demand (VoD) service is provisioned through streaming sessions established among neighboring STBs following a Peer-to-Peer fashion. Up to now the majority of research works have focused on the design and optimization of content replicas mechanisms to minimize server costs. The optimization of replicas mechanisms has been typically performed either considering very crude system performance indicators or analyzing asymptotic behavior. In this work, instead, we propose an analytical model that complements previous works providing fairly accurate predictions of system performance (i.e., blocking probability). Our model turns out to be a highly scalable, flexible, and extensible tool that may be helpful both for designers and developers to efficiently predict the effect of system design choices in large scale STB-VoD system
Mobile-Based Video Caching Architecture Based on Billboard Manager
Video streaming services are very popular today. Increasingly, users can now
access multimedia applications and video playback wirelessly on their mobile
devices. However, a significant challenge remains in ensuring smooth and
uninterrupted transmission of almost any size of video file over a 3G network,
and as quickly as possible in order to optimize bandwidth consumption. In this
paper, we propose to position our Billboard Manager to provide an optimal
transmission rate to enable smooth video playback to a mobile device user
connected to a 3G network. Our work focuses on serving user requests by mobile
operators from cached resource managed by Billboard Manager, and transmitting
the video files from this pool. The aim is to reduce the load placed on
bandwidth resources of a mobile operator by routing away as much user requests
away from the internet for having to search a video and, subsequently, if
located, have it transferred back to the user.Comment: 8 pages, 1 figure, GridCom-201
MSPlayer: Multi-Source and multi-Path LeverAged YoutubER
Online video streaming through mobile devices has become extremely popular
nowadays. YouTube, for example, reported that the percentage of its traffic
streaming to mobile devices has soared from 6% to more than 40% over the past
two years. Moreover, people are constantly seeking to stream high quality video
for better experience while often suffering from limited bandwidth. Thanks to
the rapid deployment of content delivery networks (CDNs), popular videos are
now replicated at different sites, and users can stream videos from close-by
locations with low latencies. As mobile devices nowadays are equipped with
multiple wireless interfaces (e.g., WiFi and 3G/4G), aggregating bandwidth for
high definition video streaming has become possible.
We propose a client-based video streaming solution, MSPlayer, that takes
advantage of multiple video sources as well as multiple network paths through
different interfaces. MSPlayer reduces start-up latency and provides high
quality video streaming and robust data transport in mobile scenarios. We
experimentally demonstrate our solution on a testbed and through the YouTube
video service.Comment: accepted to ACM CoNEXT'1
Decentralized Adaptive Helper Selection in Multi-channel P2P Streaming Systems
In Peer-to-Peer (P2P) multichannel live streaming, helper peers with surplus
bandwidth resources act as micro-servers to compensate the server deficiencies
in balancing the resources between different channel overlays. With deployment
of helper level between server and peers, optimizing the user/helper topology
becomes a challenging task since applying well-known reciprocity-based choking
algorithms is impossible due to the one-directional nature of video streaming
from helpers to users. Because of selfish behavior of peers and lack of central
authority among them, selection of helpers requires coordination. In this
paper, we design a distributed online helper selection mechanism which is
adaptable to supply and demand pattern of various video channels. Our solution
for strategic peers' exploitation from the shared resources of helpers is to
guarantee the convergence to correlated equilibria (CE) among the helper
selection strategies. Online convergence to the set of CE is achieved through
the regret-tracking algorithm which tracks the equilibrium in the presence of
stochastic dynamics of helpers' bandwidth. The resulting CE can help us select
proper cooperation policies. Simulation results demonstrate that our algorithm
achieves good convergence, load distribution on helpers and sustainable
streaming rates for peers
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