6,054 research outputs found
STEER: Exploring the dynamic relationship between social information and networked media through experimentation
With the growing popularity of social networks, online video services and smart phones, the traditional content consumers are becoming the editors and broadcasters of their own stories. Within the EU FP7 project STEER, project partners have developed a novel system of new algorithms and toolsets that extract and analyse social informatics generated by social networks. Combined with advanced networking technologies, the platform creates services that offer more personalized and accurate content discovery and retrieval services. The STEER system has been deployed in multiple geographical locations during live social events such as the 2014 Winter Olympics. Our use case experiments demonstrate the feasibility and efficiency of the underlying technologies
A machine learning-based framework for preventing video freezes in HTTP adaptive streaming
HTTP Adaptive Streaming (HAS) represents the dominant technology to deliver videos over the Internet, due to its ability to adapt the video quality to the available bandwidth. Despite that, HAS clients can still suffer from freezes in the video playout, the main factor influencing users' Quality of Experience (QoE). To reduce video freezes, we propose a network-based framework, where a network controller prioritizes the delivery of particular video segments to prevent freezes at the clients. This framework is based on OpenFlow, a widely adopted protocol to implement the software-defined networking principle. The main element of the controller is a Machine Learning (ML) engine based on the random undersampling boosting algorithm and fuzzy logic, which can detect when a client is close to a freeze and drive the network prioritization to avoid it. This decision is based on measurements collected from the network nodes only, without any knowledge on the streamed videos or on the clients' characteristics. In this paper, we detail the design of the proposed ML-based framework and compare its performance with other benchmarking HAS solutions, under various video streaming scenarios. Particularly, we show through extensive experimentation that the proposed approach can reduce video freezes and freeze time with about 65% and 45% respectively, when compared to benchmarking algorithms. These results represent a major improvement for the QoE of the users watching multimedia content online
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Multimedia delivery in the future internet
The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio
and video are produced, distributed, shared, managed and consumed on-line through various networks,
like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white
paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked
challenges of the Networked Media in the transition to the Future of the Internet.
Internet has evolved and changed the way we work and live. End users of the Internet have been confronted
with a bewildering range of media, services and applications and of technological innovations concerning
media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace
of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more
than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so
regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected
to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising
to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged
that in a near- to mid-term future, the Internet will provide the means to share and distribute (new)
multimedia content and services with superior quality and striking flexibility, in a trusted and personalized
way, improving citizens’ quality of life, working conditions, edutainment and safety.
In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe
network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as
community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of
interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and
innovative applications “on the move”, like virtual collaboration environments, personalised services/
media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content
combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P
networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to
contribute towards such a vision.
Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6)
and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily
contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way
ahead in the area of Content Aware media delivery platforms
Network streaming and compression for mixed reality tele-immersion
Bulterman, D.C.A. [Promotor]Cesar, P.S. [Copromotor
An Effective Peer to Peer Video Sharing Scheme with Social Reciprocity
Online video sharing and social networking are self-fertilizing speedily in today’s Internet. Online social network users are flooding more video contents among each other. A fascinating development as it is, the operational challenge in previous video streaming systems persists, i.e., the large server load required for topping of the systems. Exploring the unique advantages of a social networking based video streaming system; it advocate utilizing social reciprocities among peers with social relationships for efficient involvement incentivization and development, so as to enable high quality video streaming with low server cost. Then why only video: because more people prefer watching videos. Videos induce people to stay longer on websites. People remember videos. It achievement social reciprocity with two give-and-take ratios at each peer: (1) peer contribution ratio (PCR), which calculates the reciprocity level between a couple of social friends, and (2) system contribution ratio (SCR), which records the give-and-take level of the user to & from the entire system. It expect efficient Peer to Peer mechanisms for video streaming using the two ratios, where each user optimally chooses which other users to seek relay help from and help in relaying video streams, respectively, based on combined evaluations of their social relationship and historical reciprocity levels. This design helps to gain effective incentives for resource contribution, load balancing among relay peers, and efficient social-aware resource scheduling, security to the videos and high prefetching accuracy.
DOI: 10.17762/ijritcc2321-8169.15071
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