Nowadays, with the evolution of digital video broadcasting, as well as, the
advent of high speed broadband networks, a new era of TV services has
emerged known as IPTV. IPTV is a system that employs the high speed
broadband networks to deliver TV services to the subscribers. From the
service provider viewpoint, the challenge in IPTV systems is how to build
delivery networks that exploits the resources efficiently and reduces the
service cost, as well. However, designing such delivery networks affected by
many factors including choosing the suitable network architecture, load
balancing, resources waste, and cost reduction. Furthermore, IPTV contents
characteristics, particularly; size, popularity, and interactivity play an
important role in balancing the load and avoiding the resources waste for
delivery networks. In this paper, we investigate the problem of resource
allocation for IPTV delivery networks over the recent architecture, peer-service area architecture. The Genetic Algorithm as an optimization tool has
been used to find the optimal provisioning parameters including storage,
bandwidth, and CPU consumption. The experiments have been conducted on
two data sets with different popularity distributions. The experiments have
been conducted on two popularity distributions. The experimental results
showed the impact of content status on the resource allocation process.

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