Method for high performance on-demand video transcoding
Video streams, either in form of on-demand streaming or live streaming, usually have to be transcoded based on the characteristics of clients' devices. Transcoding is a computationally expensive and time-consuming operation; therefore, streaming service providers currently store numerous transcoded versions of the same video to serve different types of client devices. Due to the expense of maintaining and upgrading storage and computing infrastructures, many streaming service providers recently are becoming reliant on cloud services. However, the challenge in utilizing cloud services for video transcoding is how to deploy cloud resources in a cost-efficient manner without any major impact on the quality of video streams. To address this challenge, in this paper, 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%.
1. A method for cloud-based on-demand video transcoding, comprising:
(a) providing an architecture comprising:
i. a video splitter;
ii. a transcoding task scheduler;
iii. at least one transcoding virtual machine, comprising a local queue;
iv. an elasticity manager;
v. a video merger; and
vi. a caching policy;
(b) the video splitter receiving at least one video stream;
(c) the video splitter splitting the video stream into at least one Group of Pictures that can be independently transcoded;
(d) treating each said Group of Pictures as a task with an individual deadline, wherein the deadline is the presentation time of the first frame in the pertinent said Group of Pictures;
(e) the transcoding task scheduler mapping said Group of Pictures to transcoding servers by interleaving said Group of Pictures into a scheduling queue;
(f) the elasticity manager monitors the transcoding virtual machines;
(g) the elasticity manager enforces dynamic resource provisioning policies and resource provisioning policies;
(h) the video merger places all transcoded and said Group of Pictures in the correct order to generate a transcoded video stream; and
(i) the video merger sends the transcoded video stream to a video repository.
2. The method of claim 1 , wherein the transcoding task scheduler maps said Group of Pictures to transcoding servers by interleaving said Group of Pictures into a scheduling queue, comprising:
(a) if a space is available in the local queue, the transcoding task scheduler maps said Group of Pictures to the transcoding virtual machines until the local queue is full;
(b) the transcoding virtual machines notifying the transcoding task scheduler when there is space in the local queue; and
(c) mapping said Group of Pictures on a first come, first serve basis.
3. The method of claim 1 , wherein the resource provisioning policy is utilized during a provisioning event.