Exploiting virtualization for delivering cloud-based IPTV services

Cloud computing is a new infrastructure environment that delivers on the promise of supporting on-demand services in a flexible manner by scheduling bandwidth, storage and compute resources on the fly. IPTV services like Video On Demand (VoD) and Live broadcast TV requires substantial bandwidth and compute resources to meet the real time requirements and to handle the very bursty resource requirements for each of these services. To meet the needs of the bursts of requests, each with a deadline constraint for both VoD and LiveTV channel changes, we propose a resource provisioning framework that allows these services to co-exist on a common infrastructure by taking advantage of virtualization. We propose an optimal algorithm that provides the minimum number of servers needed to fulfill all requests for these services. We prove this optimality in a general setting for any number of services with general deadline constraints. By using real world data from an operational IPTV environment, our results show that anticipating and thereby enabling the delaying of VoD requests by up to 30 seconds gives significant resource savings even under conservative environmental assumptions. We also experiment with different scenarios (by varying the deadline constraints, changing the peak to average ratios of the constituent services) to compute the overall savings.