att_abstract={{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.}},
	att_authors={va037f, xc1643, vg7777, rj2124, kr2812, vv9482},
	att_copyright_notice={{The definitive version was published in IEEE INFOCOM Cloud Computing Workshop  {{, 2011-04-10}}}},
	att_tags={scheduling,  IPTV,  virtualization,  cloud computing},
	author={Vaneet Aggarwal and Xu Chen and Vijay Gopalakrishnan and Rittwik Jana and Kadangode Ramakrishnan and Vinay Vaishampayan},
	institution={{IEEE INFOCOM Workshop on Cloud Computing }},
	title={{Exploiting Virtualization for Delivering Cloud-based IPTV Services}},