Social delivery of IPTV streams

• US 10,104,442 B2
• Filed: 02/20/2018
• Issued: 10/16/2018
• Est. Priority Date: 07/14/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Dadheech, Himanshu, Dunne, Jonathan, French, Paul B., Galvin, Jr., James P., O'Sullivan, Patrick J.
• Primary Examiner(s): Langhnoja, Kunal
• Application Number:
  US15/899,544
• Publication Number:
  US 20180176657A1
• Time in Patent Office: 238 Days
• CPC Class Codes: H04N 21/24 Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth, upstream requests monitoring of server performance or load G06F11/34; arrangements for observation, testing or troubleshooting for broadcast or for distribution combined with broadcast H04H20/12
• CPC Class Codes: H04N 21/251 Learning process for intelligent management, e.g. learning user preferences for recommending movies details of learning user preferences for the retrieval of video data in a video database G06F16/739; computer systems using learning methods G06N3/08
• CPC Class Codes: H04N 21/25866 Management of end-user data customer care in data networks H04L41/5077
• CPC Class Codes: H04N 21/2668 Creating a channel for a dedicated end-user group, e.g. insertion of targeted commercials based on end-user profiles information retrieval from the Internet by querying with filtering and personalisation G06F16/9535; arrangements for replacing or switching information during the broadcast H04H20/10; push services over packet-switching network H04L12/1859; adaptation of message content in packet-switching networks H04L51/063
• CPC Class Codes: H04N 21/6175 involving transmission via Internet broadcast-related systems characterised by the transmission system being the Internet H04H60/82
• CPC Class Codes: H04N 21/6338 directed to network
• CPC Class Codes: H04N 21/64322 IP
• CPC Class Codes: H04N 21/64738 Monitoring network characteristics, e.g. bandwidth, congestion level data switched network analysis H04L41/14; monitoring functioning in data switched networks H04L43/0817; flow control in packet networks H04L47/10
• CPC Class Codes: H04N 21/64761 directed to the server

Abstract

Delivery of internet protocol television (IPTV) content, in one aspect, may comprise monitoring social media streams. Trends may be identified from the social media streams, the trends describing interests in IPTV content by location, time and subscriber types. Information may be received associated with a schedule for delivering the IPTV content. The trends may be compared with the received information to predict an expected demand of the IPTV content at the time at different locations and by different subscriber types. Resources may be reallocated to meet the expected demand in delivering the IPTV content to the different subscriber types at the different locations and the time.

Claims

1. A non-transitory computer readable storage medium storing a program of instructions executable by a machine to perform a method of delivery of Internet protocol television (IPTV) content, the method comprising:

monitoring, by at least one processor, social media streams;

receiving, by the at least one processor, information associated with a schedule for delivering the IPTV content, the schedule comprising a real-time event occurring at a particular time for real-time viewing of the real-time event, wherein the IPTV content comprises the real-time event occurring at the particular time that has been scheduled;

identifying trends from the social media streams comprising filtering the social media streams by a set of IPTV scheduled content specified in the information, the trends determined by analyzing the social media streams describing interests in IPTV content by location, time and subscription types, the subscription types comprising an Internet streamer, a high definition subscription, video on demand subscriber and a group subscription, the trend identifying a pattern of bandwidth usage in a particular area at the particular time for viewing the scheduled real-time event;

comparing, by the at least one processor, the trends with the received information to predict an expected demand of the IPTV content at the particular time at different locations and by different subscription types, the expected demand measured in terms of the locations, number of people at the locations and a breakdown of the subscription types at the locations; and

reallocating, by the at least one processor, resources to meet the expected demand in delivering the IPTV content to the different subscription types at the different locations and the time, the reallocating resources comprising at least one selected from the group consisting of adding computer memory, network bandwidth, and processing power, wherein network resource capacities are automatically reallocated without user interaction, to the high definition subscription type before reallocating to the Internet streaming subscription type,

wherein resource allocating is determined in a self-optimizing IPTV system based on social contents available online, the self-optimizing IPTV system predicting based on the social contents available the expected demand and allocating and reallocating the resources based on the expected demand,

the self-optimizing IPTV system training an algorithm for predicting the expected demand, and measuring success of the algorithm for distribution of the resources based on the expected demand over time for training the algorithm over time.

2. The non-transitory computer readable storage medium of claim 1, wherein the receiving information associated with a schedule for delivering the IPTV content comprises receiving information associated with video on demand requests for the IPTV content in the different locations.

3. The non-transitory computer readable storage medium of claim 1, wherein the reallocating resources comprises redistributing network and computer resources in networks that deliver the IPTV content to the different locations.

4. The non-transitory computer readable storage medium of claim 1, further comprising planning to renovate an infrastructure for meeting the expected demand.

5. The non-transitory computer readable storage medium of claim 1, further comprising delivering the IPTV content via the reallocated resources.

6. The non-transitory computer readable storage medium of claim 1, wherein the social media streams comprise data communicated in at least one selected from the group consisting of social networking site, micro-blogging site, news streaming site, media site, and data obtained via search engines.

7. The non-transitory computer readable storage medium of claim 1, wherein the reallocating of the resources is based on at least one selected from the group consisting of scalability, renovation, redundancy infrastructure, and maximizing quality of service to the subscriber types.

8. The non-transitory computer readable storage medium of claim 1, wherein the IPTV content is delivered as at least one selected from the group consisting of video-on-demand (VOD), live television, video recording, time-shifted television, subscription VOD service, and high definition video subscription.

9. A system for delivery of internet protocol television (IPTV) content, comprising:

a hardware processor; and

a storage device,

the hardware processor operable to perform;

monitoring, by at least one processor, social media streams;

receiving, by the at least one processor, information associated with a schedule for delivering the IPTV content, the schedule comprising a real-time event occurring at a particular time for real-time viewing of the real-time event, wherein the IPTV content comprises the real-time event occurring at the particular time that has been scheduled;

identifying trends from the social media streams comprising filtering the social media streams by a set of IPTV scheduled content specified in the information and store the trends on the storage device, the trends determined by analyzing the social media streams describing interests in IPTV content by location, time and subscription types, the subscription types comprising an Internet streamer, a high definition subscription, video on demand subscriber and a group subscription, the trend identifying a pattern of bandwidth usage in a particular area at the particular time for viewing the scheduled real-time event;

comparing, by the at least one processor, the trends with the received information to predict an expected demand of the IPTV content at the particular time at different locations and by different subscription types, the expected demand measured in terms of the locations, number of people at the locations and a breakdown of the subscription types at the locations; and

reallocating, by the at least one processor, resources to meet the expected demand in delivering the IPTV content to the different subscription types at the different locations and the time, the reallocating resources comprising at least one selected from the group consisting of adding computer memory, network bandwidth, and processing power, wherein network resource capacities are automatically reallocated without user interaction, to the high definition subscription type before reallocating to the Internet streaming subscription type,

wherein resource allocating is determined in a self-optimizing IPTV system based on social contents available online, the self-optimizing IPTV system predicting based on the social contents available the expected demand and allocating and reallocating the resources based on the expected demand,

the self-optimizing IPTV system training an algorithm for predicting the expected demand, and measuring success of the algorithm for distribution of the resources based on the expected demand over time for training the algorithm over time.

10. The system of claim 9, wherein the hardware processor receiving information associated with a schedule for delivering the IPTV content comprises the hardware processor receiving information associated with video on demand requests for the IPTV content in the different locations.

11. The system of claim 9, wherein the hardware processor reallocating resources comprises the hardware processor redistributing network and computer resources in networks that deliver the IPTV content to the different locations.

12. The system of claim 9, wherein the hardware processor further plans to renovate an infrastructure for meeting the expected demand.

13. The system of claim 9, wherein the hardware processor further delivers the IPTV content via the reallocated resources.

14. The system of claim 9, wherein the social media streams comprise data communicated in at least one selected from the group consisting of social networking site, micro-blogging site, news streaming site, media site, and data obtained via search engines.

15. The system of claim 9, wherein the hardware processor reallocates the resources based on at least one selected from the group consisting of scalability, renovation, redundancy infrastructure, and maximizing quality of service to the subscriber types.

16. The system of claim 9, wherein the IPTV content is delivered as at least one selected from the group consisting of video-on-demand (VOD), live television, video recording, time-shifted television, subscription VOD service, and high definition video subscription.