4 research outputs found

    CCN-TV: a data-centric approach to real-time video services

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    International audienceContent-Centric Networking (CCN) is a promising data-centric architecture, based on in-network caching, name-driven routing, and receiver-initiated sessions, which can greatly enhance the way Internet resources are currently used, making support for a broader set of users with increasing traffic demands possible. The CCN vision is, currently, attracting the attention of many researchers across the world, since it has all the potential to become ready to the market, to be gradually deployed in the Internet of today, and to facilitate a graceful transition from a host-centric networking rationale to a more effective data-centric working behaviour. At the same time, several issues have to be investigated before CCN can be safely deployed at the Internet scale. They include routing, congestion control, caching operations, name-space planning, and application design. With reference to application-related facets, it is worth noticing that the demand for TV services is growing at an exponential rate over time, thus requiring a very careful analysis of their performance in CCN architectures. To this end, in the present contribution we deploy a CCNTV system, capable of delivering real-time streaming TV services, and we evaluate its performance through a simulation campaign based on real-world topologies

    Providing crowd-sourced and real-time media services through a NDN-based platform

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    International audienceThe diffusion of social networks and broadband technologies is letting emerge large online communities of people that stay always in touch with each other and exchange messages, thoughts, photos, videos, files, and any other type of contents. At the same time, due to the introduction of crowd-sourcing strategies, according to which services and contents can be obtained by soliciting contributions from a group of users, the amount of data generated and exchanged within a social community may experience a radical increment never seen before. In this context, it becomes essential to guarantee resource scalability and load balancing to support real time media delivery. To this end, the present book chapter aims at investigating the design of a network architecture, based on the emerging Named Data Networking (NDN) paradigm, providing crowd-sourced real-time media contents. Such an architecture is composed by four different entities: a very large group of heterogeneous devices that produce media contents to be shared, an equally large group of users interested in them, a distributed Event Management System that creates events and handles the social community, and a NDN communication infrastructure able to efficiently manage users requests and distribute multimedia contents. To demonstrate the effectiveness of the proposed approach, we have evaluate its performance through a simulation campaign using real-world topologies
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