25,618 research outputs found
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
iTeleScope: Intelligent Video Telemetry and Classification in Real-Time using Software Defined Networking
Video continues to dominate network traffic, yet operators today have poor
visibility into the number, duration, and resolutions of the video streams
traversing their domain. Current approaches are inaccurate, expensive, or
unscalable, as they rely on statistical sampling, middle-box hardware, or
packet inspection software. We present {\em iTelescope}, the first intelligent,
inexpensive, and scalable SDN-based solution for identifying and classifying
video flows in real-time. Our solution is novel in combining dynamic flow rules
with telemetry and machine learning, and is built on commodity OpenFlow
switches and open-source software. We develop a fully functional system, train
it in the lab using multiple machine learning algorithms, and validate its
performance to show over 95\% accuracy in identifying and classifying video
streams from many providers including Youtube and Netflix. Lastly, we conduct
tests to demonstrate its scalability to tens of thousands of concurrent
streams, and deploy it live on a campus network serving several hundred real
users. Our system gives unprecedented fine-grained real-time visibility of
video streaming performance to operators of enterprise and carrier networks at
very low cost.Comment: 12 pages, 16 figure
Asynchronous displays for multi-UV search tasks
Synchronous video has long been the preferred mode for controlling remote robots with other modes such as asynchronous control only used when unavoidable as in the case of interplanetary robotics. We identify two basic problems for controlling multiple robots using synchronous displays: operator overload and information fusion. Synchronous displays from multiple robots can easily overwhelm an operator who must search video for targets. If targets are plentiful, the operator will likely miss targets that enter and leave unattended views while dealing with others that were noticed. The related fusion problem arises because robots' multiple fields of view may overlap forcing the operator to reconcile different views from different perspectives and form an awareness of the environment by "piecing them together". We have conducted a series of experiments investigating the suitability of asynchronous displays for multi-UV search. Our first experiments involved static panoramas in which operators selected locations at which robots halted and panned their camera to capture a record of what could be seen from that location. A subsequent experiment investigated the hypothesis that the relative performance of the panoramic display would improve as the number of robots was increased causing greater overload and fusion problems. In a subsequent Image Queue system we used automated path planning and also automated the selection of imagery for presentation by choosing a greedy selection of non-overlapping views. A fourth set of experiments used the SUAVE display, an asynchronous variant of the picture-in-picture technique for video from multiple UAVs. The panoramic displays which addressed only the overload problem led to performance similar to synchronous video while the Image Queue and SUAVE displays which addressed fusion as well led to improved performance on a number of measures. In this paper we will review our experiences in designing and testing asynchronous displays and discuss challenges to their use including tracking dynamic targets. © 2012 by the American Institute of Aeronautics and Astronautics, Inc
Scalable Database Access Technologies for ATLAS Distributed Computing
ATLAS event data processing requires access to non-event data (detector
conditions, calibrations, etc.) stored in relational databases. The
database-resident data are crucial for the event data reconstruction processing
steps and often required for user analysis. A main focus of ATLAS database
operations is on the worldwide distribution of the Conditions DB data, which
are necessary for every ATLAS data processing job. Since Conditions DB access
is critical for operations with real data, we have developed the system where a
different technology can be used as a redundant backup. Redundant database
operations infrastructure fully satisfies the requirements of ATLAS
reprocessing, which has been proven on a scale of one billion database queries
during two reprocessing campaigns of 0.5 PB of single-beam and cosmics data on
the Grid. To collect experience and provide input for a best choice of
technologies, several promising options for efficient database access in user
analysis were evaluated successfully. We present ATLAS experience with scalable
database access technologies and describe our approach for prevention of
database access bottlenecks in a Grid computing environment.Comment: 6 pages, 7 figures. To be published in the proceedings of DPF-2009,
Detroit, MI, July 2009, eConf C09072
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