Meeting service level agreement cost-effectively for video-on-demand applications in the cloud

Increasingly video-on-demand (VoD) applications have been ported to cloud platforms. Leveraging the elastic resource provisioning of the cloud, it is believed that VoD applications should attain high performance cost-effectively. In this paper we propose an approach that aims to solve the fundamental resource reservation and scheduling problem of configuring the cloud utility to meet SLAs for VoD applications at a modest cost. First, we devise a constraint-based model that describes the relationship among channel placement, user groups' bandwidth allocation, operating costs and QoS constraints. Second, we present a distributed heuristic algorithm, called DREAM, that solves the model and produces a budget solution that reserves and allocates cloud bandwidth, and determines the channel layout among datacenters. Simulations driven by data traces collected from a commercial VoD system demonstrate that DREAM provides much better access locality and data availability than and comparable streaming quality to state-of-the-art solutions at lower cloud operating costs.