Netflix Inc.

Andrew Berglund

Zhi Li

David Pfitzner

Te-Yuan Huang

Jeffrey Davis

Chaitanya Ekanadham

In various embodiments, a hindsight application computes a total download size for a sequence of encoded chunks associated with a media title for evaluation of at least one aspect of a video streaming service. The hindsight application computes a feasible download end time associated with a source chunk of the media title based on a network throughput trace and a subsequent feasible download end time associated with a subsequent source chunk of the media title. The hindsight application then selects an encoded chunk associated with the source chunk based on the network throughput trace, the feasible download end time, and a preceding download end time associated with a preceding source chunk of the media title. Subsequently, the hindsight application computes the total download size based on the number of encoded bits included in the first encoded chunk. The total download size correlates to an upper bound on visual quality.

Techniques for evaluating a video rate selection algorithm based on a greedy optimization of total download size over a completed streaming session

One embodiment of the present invention sets forth a technique for generating one or more hash data structures. The technique includes generating a hash data structure having entries that correspond to a plurality of content servers, and, for each file included in a first plurality of files, allocating the file to one or more content servers included in the plurality of content servers by comparing a hash value associated with the file to one or more entries included in the entries. The technique further includes comparing a network bandwidth utilization of a first content server to a network bandwidth utilization associated with one or more other content servers included in the plurality of content servers to generate a result, and modifying a first number of entries associated with the first content server and included in the entries based on the result to generate a biased hash data structure.

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Palo Alto, CA, United States of America

Andrew Berglund