System for high performance on-demand video transcoding

Inventors

Bayoumi, Magdy A. • Li, Xiangbo • Salehi, Mohsen Amini

Assignees

Louisiana Lafayette, University of • University of Louisiana at Lafayette

Abstract

The Cloud-based Video Streaming Service (CVSS) architecture is disclosed to transcode video streams in an on-demand manner. The architecture provides a platform for streaming service providers to utilize cloud resources in a cost-efficient manner and with respect to the Quality of Service (QoS) demands of video streams. In particular, the architecture includes a QoS-aware scheduling method to efficiently map video streams to cloud resources, and a cost-aware dynamic (i.e., elastic) resource provisioning policy that adapts the resource acquisition with respect to the video streaming QoS demands. Simulation results based on realistic cloud traces and with various workload conditions, demonstrate that the CVSS architecture can satisfy video streaming QoS demands and reduces the incurred cost of stream providers up to 70%.

Core Innovation

The invention provides a system for performing on-demand cloud-based transcoding of video streams that includes a video splitter, a transcoding task scheduler, at least one transcoding virtual machine, an elasticity manager, a video merger, a video repository, and a caching policy. The video splitter processes at least one video stream by splitting it into segments with at least one Group of Pictures that can be individually transcoded, so the segments are transcoded with one said Group of Pictures. The transcoding task scheduler does not comprise prior knowledge of an arrival pattern of Groups of Pictures to the system.

The system uses at least one transcoding virtual machine located on a physical server and comprising a local queue. The elasticity manager comprises at least one dynamic resource provisioning policy, wherein the dynamic resource provisioning policy performs remedial resource provisioning. The dynamic resource provisioning policies further comprise functionality to predict a deadline miss rate that will occur at a subsequent provisioning event.

After transcoding, the system merges the transcoded segments using the video merger and stores/uses data via the video repository and caching policy. The overall architecture targets on-demand cloud-based transcoding by treating Groups of Pictures as independently transcodable units for scheduling and by coordinating elasticity decisions with predicted future deadline miss rate for subsequent provisioning events.

Claims Coverage

Independent claim clm-00001 covers a cloud-based on-demand transcoding system with a splitter that generates independently transcodable Groups of Pictures, a task scheduler without prior arrival-pattern knowledge, an elasticity manager with dynamic resource provisioning that includes remedial provisioning and predicts a subsequent deadline miss rate, and a VM-based transcoding setup with a local queue plus merger and caching components.

Overall claim coverage is centered on splitting video into individually transcodable Groups of Pictures, scheduling transcoding without prior arrival-pattern knowledge, and performing elastic scaling via dynamic resource provisioning that both performs remedial provisioning and predicts a subsequent provisioning-event deadline miss rate, with transcoding executed on VMs that include a local queue and with transcoded segments merged and managed using a repository and caching policy.

Stated Advantages

Documented Applications