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Book Sections Year : 2015

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


The 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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Dates and versions

hal-00906475 , version 1 (19-11-2013)



Giuseppe Piro, Vincenzo Ciancaglini, Riccardo Loti, Luigi Alfredo Grieco, Luigi Liquori. Providing crowd-sourced and real-time media services through a NDN-based platform. Fatos Xhafa. MODELLING AND PROCESSING FOR NEXT GENERATION BIG DATA TECHNOLOGIES AND APPLICATIONS, Springer, pp.405-441, 2015, Modeling and Processing for Next-Generation Big-Data Technologies, With Applications and Case Studies, ⟨10.1007/978-3-319-09177-8⟩. ⟨hal-00906475⟩


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