System and method for adaptive delivery of rich media content to a user in a network based on real time bandwidth measurement & prediction according to available user bandwidth

• US 6,848,004 B1
• Filed: 11/23/1999
• Issued: 01/25/2005
• Est. Priority Date: 11/23/1999
• Status: Expired due to Term

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Menon, Jai, Chen, Shu-Chen Jeane, Chang, Sih-Pin Subrina, Zhang, Liang-Jie, Lipscomb, James S., Kumar, Keeranoor G.
• Primary Examiner(s): Vaughn, Jr., William C.
• Application Number:
  US09/447,585
• Time in Patent Office: 1,890 Days
• Field of Search: 709/231, 709/226, 709/225, 709/224, 709/228, 709/219, 709/223, 709/230, 709/232, 709/233, 709/234, 709/235, 370/229, 370/230, 370/231, 370/477, 370/431, 370/232, 370/233, 370/234, 719/315, 719/316, 719/332
• US Class Current: 709/232
• CPC Class Codes: H04L 65/1101 Session protocols
• CPC Class Codes: H04L 65/70 Media network packetisation
• CPC Class Codes: H04L 65/80 Responding to QoS
• CPC Class Codes: H04N 21/2662 Controlling the complexity of the video stream, e.g. by scaling the resolution or bitrate of the video stream based on the client capabilities
• CPC Class Codes: H04N 21/44209 Monitoring of downstream path of the transmission network originating from a server, e.g. bandwidth variations of a wireless network arrangements for maintenance or administration in data switching networks involving bandwidth and capacity management H04L41/0896
• CPC Class Codes: H04N 21/4437 Implementing a Virtual Machine [VM] virtual machines in general G06F9/45533
• CPC Class Codes: H04N 21/4621 Controlling the complexity of the content stream or additional data, e.g. lowering the resolution or bit-rate of the video stream for a mobile client with a small screen arrangements for using the results of monitoring on user's side in broadcast systems H04H60/65; flow control in packet networks H04L47/10
• CPC Class Codes: H04N 21/85406 involving a specific file format, e.g. MP4 format
• CPC Class Codes: H04N 21/8545 for generating interactive applications

Abstract

A network implementing HotMedia architecture provides real time measurement and prediction of bandwidth for adaptive content delivery of rich media according to available user bandwidth. The rich media file created at the creation station is transmitted by the delivery station to the client station in steaming Java applets having a framework including a thumbnail frame and a media frame. In real-time, the client station detects the bandwidth used by the Java applet; predicts the available bandwidth for next media delivery based on the detected bandwidth and fetches the corresponding sensitive bandwidth media fame from a web server according to a linear or non-linear prediction algorithm resulting in bandwidth sensitive rich media content delivery from the delivery station to the client station for display and user interaction.

Claims

1. A network using a rich media authoring tool architecture and including a content delivery station and a client station for adaptive delivery of rich media content to the client station for user interaction based on real time bandwidth measurement and prediction according to available user bandwidth, comprising:

(a) means for creating rich media content in a streaming file having a framework including at least a thumbnail frame and a media frame;

(b) means for transmitting the streaming files through object oriented programming language applets;

(c) means for calculating a first detected bandwidth measurement B1 based on a thumbnail frame size in bits divided by a time T1 or a thumbnail frame loading time;

(d) means for calculating a second detect bandwidth measurement B2 based on an object oriented programming language class size divided by a time T2 or an object oriented programming language class loading time;

(e) means for predicting a bandwidth B3 for a next available rich media content delivery based a media frame size dived by a time T3 or a media frame loading time;

(f) means for predicting succeeding next available bandwidth base on a discrete time series where Bi (i=1, 2, . . . ) and B*(i+1)=f(Bi, Bi−

1(i>

=3) where f is a mapping operator; and

(g) decision maker means for choosing an appropriate media content for delivery to the client station according to a predicted available bandwidth B*(i+1).

2. The network as described in claim 1 wherein the mapping operator f can be any appropriate linear or no-linear mapping including artificial neural network and fuzzy logic reasoning.

3. The network as described in claim 1 wherein the decision maker can be on either the client station or the content delivery station.

4. The network as described in claim 3 wherein the decision maker on the client station further comprises:

(a) means for making a decision based on the predicted available user bandwidth in the client station;

(b) means for sending decision information from the client station to the content delivery station through an http request;

(c) means for fetching the appropriate media content directly based on the predicted available user bandwidth; and

(d) means for receiving the appropriate media content as a response of the http request made by the client station.

5. The network as described in claim 3 wherein the decision maker on the content delivery station further comprises:

(a) means for sending the predicted available user bandwidth from the client station to the content delivery station through an http request;

(b) means for making a decision based on a received predicted available user bandwidth; and

(c) means for delivering the appropriate media content to the client station.

6. The network as described in claim 1 wherein the steaming file comprises multiple media frames without a thumbnail frame.

7. The network as described in claim 1 wherein the appropriate media content comprises any web elements.

8. The network as described in claim 1 wherein the appropriate media content comprises any media frame in the same streaming file.

9. The network as described in claim 1 wherein the appropriate media content comprises any media frame in another streaming file.

10. The network as described in claim 1 wherein the real time bandwidth measurement comprises a key event bandwidth measurement that is more efficient and effective than all time bandwidth monitoring.

11. In a network using a rich media authoring tool architecture and including a content delivery station and a client station for adaptive delivery of rich media content to the client station for user interaction based on real time bandwidth measurement and prediction according to available user bandwidth, comprising the steps of:

(a) creating rich media content in a streaming file having a framework including at least a thumbnail frame and a media frame;

(b) transmitting the streaming files through object oriented programming language applets;

(c) calculating a first detected bandwidth measurement B1 based on a thumbnail frame size in bits divided by a time T1 or a thumbnail frame loading time;

(d) calculating a second detect bandwidth measurement B2 based on an object oriented programming language class size divided by a time T2 or an object oriented programming language class loading time;

(e) predicting a bandwidth B3 for a next available rich media content delivery based a media frame size dived by a time T3 or a media frame loading time;

(f) predicting succeeding next available bandwidth base on a discrete time series where Bi(i=1, 2, . . . ) and B*(i+1)=f(Bi, Bi−

1 (i>

=3) where f is a mapping operator; and

(g) a decision maker choosing an appropriate media content for delivery to the client station according to a predicted available bandwidth B*(i+1).

12. The method of claim 11 wherein the decision maker on the client station further comprising the steps of:

(a) making a decision based on the predicted available user bandwidth in the client station;

(b) sending decision information from the client station to the content delivery station through an http request;

(c) fetching the appropriate media content directly based on the predicted available user bandwidth; and

(d) receiving the appropriate media content as a response of the http request made by the client station.

13. The method of claim 11 wherein the decision maker on the content delivery station further comprising the steps of:

(a) sending the predicted available user bandwidth from the client station to the content delivery station through an http request;

(b) making a decision based on a received predicted available user bandwidth; and

(c) means for delivering the appropriate media content to the client station.

14. The method of claim 11 wherein the mapping operator f can be any appropriate linear or no-linear mapping including artificial neural network and fuzzy logic reasoning.

15. The method of claim 11 wherein the appropriate media content comprises any media frame in the same streaming file.

16. The method of claim 11 wherein the appropriated media content comprises any media frame in another streaming file.

17. The method of claim 11 wherein the real time bandwidth measurement comprises a key event bandwidth measurement that is more efficient and effective than all time bandwidth monitoring.