Methods and apparatus to predict end of streaming media using a prediction model

• US 10,193,785 B2
• Filed: 04/16/2018
• Issued: 01/29/2019
• Est. Priority Date: 08/29/2014
• Status: Active Grant

• Current Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Original Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Inventors: Besehanic, Jan
• Primary Examiner(s): Gillis, Brian J.
• Assistant Examiner(s): Guzman, Javier O
• Application Number:
  US15/954,552
• Publication Number:
  US 20180234321A1
• Time in Patent Office: 288 Days
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 43/0894 Packet rate
• CPC Class Codes: H04L 43/106 using time related information in packets, e.g. by adding timestamps
• CPC Class Codes: H04L 47/823 Prediction of resource usage
• CPC Class Codes: H04L 47/83 based on usage prediction
• CPC Class Codes: H04L 65/60 Network streaming of media packets
• CPC Class Codes: H04L 65/612 for unicast
• CPC Class Codes: H04N 21/2402 Monitoring of the downstream path of the transmission network, e.g. bandwidth available traffic monitoring in data switching networks H04L43/00; monitoring data switching networks utilization H04L43/0876
• CPC Class Codes: H04N 21/8456 by decomposing the content in the time domain, e.g. in time segments

Abstract

Apparatus to predict end of streaming media using a prediction model are disclosed herein. Examples disclosed herein comprise a predictor to determine a bandwidth rate associated with presentation of streaming media based on monitored traffic between a user device and the streaming media, a modeler to generate a prediction model based on characteristics of the bandwidth rate, and a forecaster to determine that a time when an output of the prediction model is below a minimum bandwidth threshold is a session end time for a streaming media session, the session end time corresponding to when the user device stops receiving the streaming media.

Claims

1. An apparatus comprising:

a predictor to determine a bandwidth rate associated with presentation of streaming media based on monitored traffic between a user device and a streaming media distributor;

a modeler to generate a prediction model based on characteristics of the bandwidth rate, the characteristics of the bandwidth rate including an amplitude of the bandwidth rate, a mean value of the bandwidth rate, and a standard deviation of the bandwidth rate; and

a forecaster to determine that a time when an output of the prediction model is below a minimum bandwidth threshold is a session end time for a streaming media session, the session end time corresponding to when the user device stops receiving the streaming media.

2. The apparatus of claim 1, further including:

an identifier to determine a type of the streaming media presented on the user device; and

a threshold generator to set a bandwidth threshold based on the type of the streaming media.

3. The apparatus of claim 2, wherein the type of the streaming media is at least one of video and audio.

4. The apparatus of claim 2, further including a parameter generator to determine a decay factor for the prediction model based on the type of the streaming media.

5. The apparatus of claim 4, wherein the parameter generator is further to calculate prediction model parameters by:

determining the mean value of the bandwidth rate;

determining the amplitude of the bandwidth rate; and

determining the standard deviation of the bandwidth rate.

6. The apparatus of claim 1, wherein the bandwidth rate further includes a timestamp associated with the bandwidth rate.

7. The apparatus of claim 1, wherein the bandwidth rate is not received from a proxy that is intermediate to a streaming media application presenting the streaming media and is not received from a streaming media distributor transmitting the streaming media to the streaming media application.

8. An apparatus, comprising:

means for determining a bandwidth rate associated with presentation of streaming media based on monitored traffic between a user device and a streaming media distributor;

means for generating a prediction model based on characteristics of the bandwidth rate, the characteristics of the bandwidth rate including an amplitude of the bandwidth rate, a mean value of the bandwidth rate, and a standard deviation of the bandwidth rate; and

means for determining that a time when an output of the prediction model is below a minimum bandwidth threshold is a session end time for a streaming media session, the session end time corresponding to when the user device stops receiving the streaming media.

9. The apparatus of claim 8, further including:

means for determining a type of the streaming media presented on the user device; and

means for setting a bandwidth threshold based on the type of the streaming media.

10. The apparatus of claim 9, wherein the type of the streaming media is at least one of video and audio.

11. The apparatus of claim 9, further including means for determining a decay factor for the prediction model based on the type of the streaming media.

12. The apparatus of claim 11, further including means for calculating prediction model parameters by:

determining the mean value of the bandwidth rate;

determining the amplitude of the bandwidth rate; and

determining the standard deviation of the bandwidth rate.

13. The apparatus of claim 8, wherein the bandwidth rate further includes a timestamp associated with the bandwidth rate.

14. The apparatus of claim 8, wherein the bandwidth rate is not received from a proxy that is intermediate to a streaming media application presenting the streaming media and is not received from a streaming media distributor transmitting the streaming media to the streaming media application.

15. A non-transitory computer readable medium comprising instructions that, when executed, cause a machine to, at least:

determine a bandwidth rate associated with presentation of streaming media based on monitored traffic between a user device and a streaming media distributor;

generate a prediction model based on characteristics of the bandwidth rate, the characteristics of the bandwidth rate including an amplitude of the bandwidth rate, a mean value of the bandwidth rate, and a standard deviation of the bandwidth rate; and

determine that a time when an output of the prediction model is below a minimum bandwidth threshold is a session end time for a streaming media session, the session end time corresponding to when the user device stops receiving the streaming media.

16. The non-transitory computer readable storage medium as defined in claim 15, further including instructions that, when executed, cause the machine to:

determine a type of the streaming media presented on the user device; and

set a bandwidth threshold based on the type of the streaming media.

17. The non-transitory computer readable storage medium of claim 16, wherein the type of the streaming media is at least one of video and audio.

18. The non-transitory computer readable storage medium as defined in claim 16, further including instructions that, when executed, cause the machine to determine a decay factor for the prediction model based on the type of the streaming media.

19. The non-transitory computer readable storage medium as defined in claim 18, further including instructions that, when executed, cause the machine to calculate prediction model parameters by:

determining the mean value of the bandwidth rate;

determining the amplitude of the bandwidth rate; and

determining the standard deviation of the bandwidth rate.

20. The non-transitory computer readable storage medium as defined in claim 15, wherein the bandwidth rate further includes a timestamp associated with the bandwidth rate.

21. The non-transitory computer readable storage medium as defined in claim 15, wherein the bandwidth rate is not received from a proxy that is intermediate to a streaming media application presenting the streaming media and is not received from a streaming media distributor transmitting the streaming media to the streaming media application.