Microsoft Technology Licensing, LLC

Netflix Inc.

Sagar Bharadwaj Kalasibail Seetharam

Xiaoqing Zhu

Yogesh Bansal

Ranjita Bhagwan

Te-Yuan Huang

Kyle Christopher Swanson

Venkata N Padmanabhan

Parth Dhaval Thakkar

Renata Cruz Teixeira

Kaylie Alexa Kwon

Vijay Rajeshkumar

Harsha Sharma

Kathleen Voelbel

In various embodiments, a simulation evaluation application generates a first streaming header based on rungs of a first candidate encoding ladder, where each rung specifies a resolution and a bitrate of a different encoded video. The simulation evaluation application executes an adaptive bitrate algorithm on the first streaming header based on a network throughput trace to determine a first value for a metric that is relevant to quality of experience. The simulation evaluation application generates a second streaming header based on a second candidate encoding ladder. The simulation evaluation application executes the adaptive bitrate algorithm on the second streaming header based on the network throughput trace to determine a second value for the metric. The simulation evaluation application compares the first value to the second value to determine that the first candidate encoding ladder instead of the second candidate encoding ladder should be used to stream the media title.

Simulation-based techniques for evaluating encoding ladders for video streaming

The techniques disclosed herein provision inter-DC WAN capacity based on network failure statistics and bandwidth demands of a cloud-hosted application. Network capacity is provisioned based on an assumption of runtime cooperation between the application and the network. For example, if the network detects that a link has failed, the application may cooperate with the network to pause a deferrable transfer, reserving bandwidth for non-deferrable transfers. With knowledge that deferrable transfers will be dynamically paused when a primary link fails, backup links may be provisioned with less capacity than the primary link. The ability to dynamically defer transfers also enables a greater degree of bandwidth smoothing, e.g. reducing peak demand by scheduling deferrable transfers for off-peak hours. This allows network links to be provisioned with less capacity than if all transfers were performed immediately.

Optimizing network provisioning through cooperation

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Pittsburgh, PA, United States of America

Sagar Bharadwaj Kalasibail Seetharam