Opportunistic block transmission with time constraints

• US 10,587,473 B2
• Filed: 10/02/2017
• Issued: 03/10/2020
• Est. Priority Date: 03/23/2005
• Status: Active Grant

• Current Assignee: Numecent Holdings Incorporated
• Original Assignee: Numecent Holdings Incorporated
• Inventors: DeVries, Jeffrey, Hitomi, Arthur S.
• Primary Examiner(s): Thai, Tuan V
• Application Number:
  US15/723,166
• Publication Number:
  US 20180026847A1
• Time in Patent Office: 890 Days
• Field of Search: 711100, 711154, 711170, 711200
• CPC Class Codes: G06F 12/0802 Addressing of a memory level in which the access to the desired data or data block requires associative addressing means, e.g. caches
• CPC Class Codes: G06F 12/0862 with prefetch
• CPC Class Codes: G06F 12/0864 using pseudo-associative means, e.g. set-associative or hashing
• CPC Class Codes: G06F 13/1673 using buffers
• CPC Class Codes: H04L 41/0896 Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities flow or congestion control using dynamic resource allocation, e.g. in-call renegotiation, H04L47/76
• CPC Class Codes: H04L 65/612 for unicast
• CPC Class Codes: H04L 65/70 Media network packetisation
• CPC Class Codes: H04L 67/5681 Pre-fetching or pre-delivering data based on network characteristics

Abstract

A technique for determining a data window size allows a set of predicted blocks to be transmitted along with requested blocks. A stream enabled application executing in a virtual execution environment may use the blocks when needed.

Claims

1. A method comprising:

receiving a request, from a streaming playback device, for a block of a stream-enabled application;

determining likelihood of each of additional blocks of the stream-enabled application being requested based on an identification of the block of the stream-enabled application using probability data;

adding the requested block of the stream-enabled application and then at least a portion of the additional blocks of the stream-enabled application to an output buffer in order of decreasing likelihoods of the additional blocks of the stream-enabled application being requested within a data window size of the output buffer, the data window size of the output buffer being varied based on at least one of a latency and a throughput that are dynamically changing;

providing the requested block of the stream-enabled application and the at least the portion of the additional blocks in the output buffer to the streaming playback device.

2. The method of claim 1, wherein the data window size is varied based on a maximum throughput with the streaming playback device.

3. The method of claim 1, wherein the at least the portion of the additional blocks does not fill the output buffer when a non-added portion of the additional blocks is unlikely to follow the requested block of the stream-enabled application.

4. The method of claim 1, wherein the probability data is a logical block probability table.

5. The method of claim 1, wherein the probability data is generated based on a probability that the at least the portion of the additional blocks of the stream-enabled application will be requested in a number of stages following a current stage in virtualizing the stream-enabled application using the requested block of the stream-enabled application.

6. The method of claim 1, wherein the data window size is varied also based on user responsiveness requirements to control a number of the additional blocks of the stream-enabled application added to the output buffer while still meeting the user responsiveness requirements in executing the stream-enabled application.

7. The method of claim 6, wherein the user responsiveness requirements include an interactivity threshold that is a limit on an amount of time that a user interacting with the streaming playback device can wait for the at least the portion of the additional blocks in virtualizing the stream-enabled application.

8. The method of claim 1, wherein the data window size is varied based on a maximum throughput with the streaming playback device and the maximum throughput is determined dynamically as the stream-enabled application is virtualized by the streaming playback device.

9. The method of claim 1, wherein the data window size is varied based on a maximum throughput with the streaming playback device and the maximum throughput is determined by running the throughput through a low pass filter to determine an average throughput, the average throughput used in determining the maximum throughput with the streaming playback device.

10. The method of claim 1, wherein the data window size is varied based on a maximum throughput with the streaming playback device and the maximum throughput is determined dynamically based on the latency with the streaming playback device.

11. A system comprising:

an interface configured to receive a request, from a streaming playback device, for a block of a stream-enabled application;

a predictor configured to determine likelihood of each of additional blocks of the stream-enabled application being requested based on an identification of the block of the stream-enabled application using probability data;

a predicted block aggregation engine configured to;

add the requested block of the stream-enabled application and then at least a portion of the additional blocks of the stream-enabled application to an output buffer in order of decreasing likelihoods of the additional blocks of the stream-enabled application being requested within a data window size of the output buffer, the data window size of the output buffer being varied based on at least one of a latency and a throughput that are dynamically changing;

the interface further configured to provide the requested block of the stream-enabled application and the at least the portion of the additional blocks in the output buffer to the streaming playback device.

12. The system of claim 11, wherein the data window size is varied based on a maximum throughput with the streaming playback device.

13. The system of claim 11, wherein the at least the portion of the additional blocks does not fill the output buffer when a non-added portion of the additional blocks is unlikely to follow the requested block of the stream-enabled application.

14. The system of claim 11, wherein the probability data is a logical block probability table.

15. The system of claim 11, wherein the probability data is generated based on a probability that the at least the portion of the additional blocks of the stream-enabled application will be requested in a number of stages following a current stage in virtualizing the stream-enabled application using the requested block of the stream-enabled application.

16. The system of claim 11, wherein the data window size is varied also based on user responsiveness requirements to control a number of the additional blocks of the stream-enabled application added to the output buffer while still meeting the user responsiveness requirements in executing the stream-enabled application.

17. The system of claim 16, wherein the user responsiveness requirements include an interactivity threshold that is a limit on an amount of time that a user interacting with the streaming playback device can wait for the at least the portion of the additional blocks in virtualizing the stream-enabled application.

18. The system of claim 11, wherein the data window size is varied based on a maximum throughput with the streaming playback device and the maximum throughput is determined dynamically as the stream-enabled application is virtualized by the streaming playback device.

19. The system of claim 11, wherein the data window size is varied based on a maximum throughput with the streaming playback device and the maximum throughput is determined by running the throughput through a low pass filter to determine an average throughput, the average throughput used in determining the maximum throughput with the streaming playback device.

20. The system of claim 11, wherein the data window size is varied based on a maximum throughput with the streaming playback device and the maximum throughput is determined dynamically based on the latency with the streaming playback device.