Integration of Multi Server for Profit Efficiency in Cloud Computing

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. It seeks to lower a provider’s costs of real-time IPTV services through a virtualized IPTV architecture and through intelligent time-shifting of service delivery. The merits of the differences in the deadlines associated with Live TV versus Video-on-Demand (VoD) to effectively multiplex these services. A generalized framework is provided for computing the amount of resources needed to support several services, without missing the deadline for any service. An optimization formulation that uses a generic cost function is build. The multiple forms for the cost function (e.g., maximum, convex and concave functions) to reflect the different pricing options are implemented. The solution to this formula gives the number of servers needed at different time instants to support these services. 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 is implemented. End results explain the load is minimized by ? 24%. There are interesting open problems in designing mechanisms that allow time-shifting of load in such environments.