Optimizing Cloud Resources for Delivering IPTV Services Through Virtualization.

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Presentation transcript:

Optimizing Cloud Resources for Delivering IPTV Services Through Virtualization

Abstract Virtualized cloud-based services can take advantage of statistical multiplexing across applications to yield significant cost savings. However, achieving similar savings with real-time ser¬vices can be a challenge. In this paper, we seek to lower a provider’s costs for real-time IPTV services through a virtualized IPTV archi¬tecture and through intelligent time-shifting of selected services.

Existing system IP-based video delivery has become very popular recently. Content and service providers typically provision their re¬sources for handling peak demands of each service across the subscriber population. However, provisioning for peak demands results in the resources being underutilized in all other periods.

Architecture Diagram

System Specification HARDWARE REQUIREMENTS Processor : intel Pentium IV Ram : 512 MB Hard Disk : 80 GB HDD SOFTWARE REQUIREMENTS Operating System : windows XP / Windows 7 FrontEnd : Java BackEnd : MySQL 5

CONCLUSION We studied how IPTV service providers can leverage a virtu¬alized cloud infrastructure by intelligently time-shifting load to better utilize deployed resources while still meeting the strict time deadlines for each individual service. We used LiveTV ICC and VoD as examples of IPTV services that can run on a shared virtualized infrastructure. Our paper first provided a generalized framework for computing the resources required to support multiple services with deadlines. We formulated the problem as an optimization problem and computed the number of servers required based on a generic cost function. We consid-ered multiple forms for the cost function of the server complex (e.g., min-max, convex and concave) and solved for the optimal number of servers required to support these services without missing any deadlines.

THANK YOU