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IEEE / Institute of Electrical and Electronics Engineers Incorporated:445 Hoes Lane:Piscataway, NJ 08854:(800)701-4333, (732)981-0060, EMAIL: [email protected], INTERNET: http://www.ieee.org, Fax: (732)981-9667
Doi
Abstract
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 systems
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