SYSTEM AND METHOD FOR DELIVERING CONTENT IN A CONTENT DELIVERY NETWORK

• US 20150012593A1
• Filed: 07/03/2013
• Published: 01/08/2015
• Est. Priority Date: 02/23/2012
• Status: Active Grant

• Current Assignee: Ericsson AB (Telefonaktiebolaget LM Ericsson)
• Original Assignee: Ericsson Television Incorporated (Telefonaktiebolaget LM Ericsson)
• Inventors: Phillips, Chris, Rodgers, Jimmie
• Granted Patent: US 9,253,051 B2
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: G06F 16/9574 of access to content, e.g. by caching
• CPC Class Codes: H04L 41/0893 Assignment of logical groups to network elements
• CPC Class Codes: H04L 41/0894 Policy-based network configuration management
• 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 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 41/5025 by proactively reacting to service quality change, e.g. by reconfiguration after service quality degradation or upgrade
• CPC Class Codes: H04L 41/509 wherein the managed service relates to media content delivery, e.g. audio, video or TV
• CPC Class Codes: H04L 43/0882 Utilisation of link capacity
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 47/20 Traffic policing
• CPC Class Codes: H04L 47/26 using explicit feedback to the source, e.g. choke packets
• CPC Class Codes: H04L 47/30 in combination with information about buffer occupancy at either end or at transit nodes
• CPC Class Codes: H04L 47/52 by attributing bandwidth to queues
• CPC Class Codes: H04L 47/70 Admission control; Resource allocation
• CPC Class Codes: H04L 47/823 Prediction of resource usage
• CPC Class Codes: H04L 47/83 based on usage prediction
• CPC Class Codes: H04L 65/61 for supporting one-way streaming services, e.g. Internet radio
• CPC Class Codes: H04L 67/5681 Pre-fetching or pre-delivering data based on network characteristics

Abstract

A content delivery method and system based on popularity-driven pre-provisioning of content in a content delivery network (CDN). In one method, a network element may obtain trend data relative to a particular content to be distributed by the CDN. The network element may also obtain demographic data of subscribers serviced by the CDN. An expected popularity distribution of the particular content is forecasted based on a metric derived from at least one of the trend data and the demographic data. A push policy for pushing and/or pre-provisioning of the content to one or more nodes of the CDN is effectuated at the network element based on the expected popularity distribution of the content relative to the geographical region serviced by the CDN.

Claims

1. A content delivery method, comprising:

obtaining trend data relative to a particular content to be distributed in a geographical region serviced by a content delivery network;

obtaining demographic data of subscribers serviced by the content delivery network;

forecasting an expected popularity distribution of the particular content in the geographical region based on a metric depending on at least one of the trend data and the demographic data; and

effectuating a push policy for pushing the particular content to one or more nodes of the content delivery network based on the expected popularity distribution of the particular content relative to the geographical region serviced by the content delivery network.

2. The method as recited in claim 1, further comprising:

obtaining licensing data relative to the particular content from a content provider;

assigning a push weight for distributing the particular content via the content delivery network based on comparing a current date against a licensing start date relative to the particular content;

provisioning a push pipe based on the push weight as part of the push policy for distributing the particular content to the one or more nodes of the content delivery network; and

providing the push policy to a central distribution node of the content delivery network.

3. The method as recited in claim 1, wherein the trend data relative to the particular content are obtained based on at least one of Internet search engine trend data and social media search trend data.

4. The method as recited in claim 3, wherein the at least one of Internet search engine trend data and social media search trend data relates to keyword search data involving one or more of terms of a plot synopsis of the particular content, a title of the particular content, and searches relating to one or more actors associated with the particular content.

5. The method as recited in claim 1, further comprising obtaining marketing data relative to the particular content and using the marketing data in the forecasting of the expected popularity distribution of the particular content.

6. The method as recited in claim 5, wherein the marketing data comprises at least one of box office revenue data, stored media sales data and related content sales data.

7. The method as recited in claim 1, wherein the push policy is configured to provision the pushing of the particular content to the one or more nodes of the content delivery network that are hierarchically organized, having one or more central distribution nodes, each central distribution node configured to serve one or more regional distribution nodes, each regional distribution node serving one or more local edge server nodes that serves a group of subscribers.

8. The method as recited in claim 1, wherein the demographic data of subscribers is obtained from at least one of a content provider database, a network operator database and a publicly available Internet database.

9. A network element configured to operate in association with a content delivery network, the network element comprising:

one or more processors;

a memory subsystem coupled to the one or more processors, the memory subsystem including a persistent memory; and

a content popularity forecasting module implemented in the persistent memory and configured to be executed by the one or more processors for performing;

obtaining trend data relative to a particular content to be distributed in a geographical region serviced by the content delivery network;

obtaining demographic data of subscribers serviced by the content delivery network;

determining an expected popularity distribution of the particular content in the geographical region based on a metric depending on at least one of the trend data and the demographic data; and

effectuating a push policy for pushing the particular content to one or more nodes of the content delivery network based on the expected popularity distribution of the particular content relative to the geographical region serviced by the content delivery network.

10. The network element as recited in claim 9, wherein the content popularity forecasting module is further configured to:

obtain licensing data relative to the particular content from a content provider;

assign a push weight for distributing the particular content via the content delivery network based on comparing a current date against a licensing start date relative to the particular content;

provision a push pipe based on the push weight as part of the push policy for distributing the particular content to the one or more nodes of the content delivery network; and

provide the push policy to a central distribution node of the content delivery network.

11. The network element as recited in claim 9, wherein the trend data relative to the particular content are obtained based on at least one of Internet search engine trend data and social media search trend data.

12. The network element as recited in claim 11, wherein the at least one of Internet search engine trend data and social media search trend data relates to keyword search data involving one or more of terms of a plot synopsis of the particular content, a title of the particular content, and searches relating to one or more actors associated with the particular content.

13. The network element as recited in claim 9, wherein the content popularity forecasting module is further configured to obtain marketing data relative to the particular content and using the marketing data in the forecasting of the expected popularity distribution of the particular content.

14. The network element as recited in claim 13, wherein the marketing data comprises at least one of box office revenue data, stored media sales data and related content sales data.

15. The network element as recited in claim 9, wherein the push policy is configured to provision the pushing of the particular content to the one or more nodes of the content delivery network that are hierarchically organized, having one or more central distribution nodes, each central distribution node configured to serve one or more regional distribution nodes, each regional distribution node serving one or more local edge server nodes that serves a group of subscribers.

16. The network element as recited in claim 9, wherein the demographic data of subscribers is obtained from at least one of a content provider database, a network operator database and a publicly available Internet database.

17. A non-transitory computer-readable medium containing instructions stored thereon which, when executed by a computer system configured to operate as a network element in association with a content delivery network, perform the acts:

obtaining trend data relative to a particular content to be distributed in a geographical region serviced by the content delivery network;

obtaining demographic data of subscribers serviced by the content delivery network;

forecasting an expected popularity distribution of the particular content in the geographical region based on a metric depending on at least one of the trend data and the demographic data; and

effectuating a push policy for pushing the particular content to one or more nodes of the content delivery network based on the expected popularity distribution of the particular content relative to the geographical region serviced by the content delivery network.

18. The non-transitory computer-readable medium as recited in claim 17, further comprising instructions for performing:

obtaining licensing data relative to the particular content from a content provider;

assigning a push weight for distributing the particular content via the content delivery network based on comparing a current date against a licensing start date relative to the particular content;

provisioning a push pipe based on the push weight as part of the push policy or distributing the particular content to the one or more nodes of the content delivery network; and

providing the push policy to a central distribution node of the content delivery network.

19. The non-transitory computer-readable medium as recited in claim 17, wherein the trend data relative to the particular content are obtained based on at least one of Internet search engine trend data and social media search trend data.

20. The non-transitory computer-readable medium as recited in claim 19, wherein the at least one of Internet search engine trend data and social media search trend data relates to keyword search data involving one or more of terms of a plot synopsis of the particular content, a title of the particular content, and searches relating to one or more actors associated with the particular content.

21. The non-transitory computer-readable medium as recited in claim 17, further comprising instructions for obtaining marketing data relative to the particular content and using the marketing data in the forecasting of the expected popularity distribution of the particular content.

22. The non-transitory computer-readable medium as recited in claim 17, wherein the marketing data comprises at least one of box office revenue data, stored media sales data and related content sales data.

23. The non-transitory computer-readable medium as recited in claim 17, wherein the push policy is configured to provision the pushing of the particular content to the one or more nodes of the content delivery network that are hierarchically organized, having one or more central distribution nodes, each central distribution node configured to serve one or more regional distribution nodes, each regional distribution node serving one or more local edge server nodes that serves a group of subscribers.

24. The non-transitory computer-readable medium as recited in claim 17, wherein the demographic data of subscribers is obtained from at least one of a content provider database, a network operator database and a publicly available Internet database.