Author : Nagalakshmi.N and A.Kannammal

A Virtualized cloud-based services can take advantage of statistical multiplexing across applications to yield significant cost savings to the operator. Achieving similar benefits with real-time services can be a challenge. Here we seek to lower a provider’s costs of real-time IPTV services through a virtualized IPTV architecture and through intelligent time-shifting of service delivery. We take merits of the differences in the deadlines associated with Live TV versus Video-on-Demand (VoD) to effectively multiplex these services. We provide a generalized framework for computing the amount of resources needed to support several services, without missing the deadline for any service. We build the problem as an optimization formulation that uses a generic cost function. We keep in mind multiple forms for the cost function (e.g., maximum, convex and concave functions) to reflect the different pricing options. The solution to this formula gives the number of servers needed at different time instants to support these services. We implement a simple logic for time-shifting scheduled jobs in a simulator and study the reduction in server load using real traces from an operational IPTV network. Our results explain that we are able to minimize the load by ∼ 24% (compared to a possible ∼ 31%). We also show that there are interesting open problems in designing mechanisms that allow time-shifting of load in such environments.

Keywords: Cloud Assets, IPTV Assistance

Article published in International Journal of Current  Engineering  and Technology, Vol.4,No.2 (April- 2014)