The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 29, 2014

Filed:

Nov. 30, 2010
Applicants:

Cheng-hsin Hsu, Mountain View, CA (US);

Nikolaos Markos Freris, Zurich-Oerlikon, CH;

Jatinder Pal Singh, Mountain View, CA (US);

Xiaoqing Zhu, Mountain View, CA (US);

Inventors:

Cheng-Hsin Hsu, Mountain View, CA (US);

Nikolaos Markos Freris, Zurich-Oerlikon, CH;

Jatinder Pal Singh, Mountain View, CA (US);

Xiaoqing Zhu, Mountain View, CA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04N 21/2662 (2011.01); H04N 7/26 (2006.01); H04N 21/2343 (2011.01); H04N 21/2381 (2011.01); H04N 21/41 (2011.01);
U.S. Cl.
CPC ...
H04N 19/002 (2013.01); H04N 19/00175 (2013.01); H04N 21/234327 (2013.01); H04N 21/2381 (2013.01); H04N 21/4126 (2013.01);
Abstract

The described system and method provide joint rate control and scalable stream adaptation for multiple clients concurrently competing for the same access networks. For each such client, an optimization problem is constructed and solved to determine the streaming rate over each access network, the video packets to be transmitted, and the access network over which each video packet is sent. The rate control and stream adaptation problem is constructed as an integer program in an embodiment of the invention, with an objective to minimize a cost function of the expected video distortion. Randomized packet scheduling is accounted for in an embodiment of the invention by relaxing the integer program into real-valued optimization programs and deriving convex programming approximations.


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