There are mainly three threads of this paper in server reqirements , namely cloud computing, scheduling with deadline constraints, and optimization. Cloud computing has recently changed the landscape of Internet based computing, a shared pool of configurable computing resources (networks, servers, storage) can be rapidly provisioned and released to support multiple services within the same infrastructure. Due to its nature of serving computationally intensive applications, cloud infrastructure is particularly suitable for content delivery applications. Typically LiveTV and VoD services are operated using dedicated servers, this paper considers the option of operating multiple services by careful rebalancing of resources in real time within the same cloud infrastructure. They consider various cost functions, evaluate the optimal server resources needed, and study the impact of each cost function on the optimal solution. Convex and concave functions. With convex functions, the cost increases slowly initially and subsequently grows faster. For concave functions, the cost increases quickly initially and then flattens out, indicating a point of diminishing unit costs (e.g., slab or tiered pricing). Minimizing a convex cost function results in averaging the number of servers (i.e., the tendency is to service requests equally throughout their deadlines so as to smooth out the requirements of the number of servers needed to serve all the requests). Minimizing a concave cost function results in finding the extremal points away from the maximum (as shown in the example below) to reduce cost. This may result in the system holding back the requests until just prior to their deadline and serving them in a burst, to get the benefit of a lower unit cost because of the concave cost function IPTV service providers can leverage a virtualized cloud infrastructure and intelligent time-shifting of load to better utilize deployed resources. Using Instant Channel Change and VoD delivery as examples, we showed that we can take advantage of the difference in workloads of IPTV services to schedule them appropriately on virtualized infrastuctures. By anticipating the LiveTV ICC bursts that occur every half hour we can speed up delivery of VoD content before these bursts by prefilling the set top box buffer. This helps us to dynamically reposition the VoD servers to accomodate ICC bursts that typically last for a very short time.