Content delivery acceleration system

• US 10,432,751 B1
• Filed: 06/04/2018
• Issued: 10/01/2019
• Est. Priority Date: 08/18/2016
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google LLC (Alphabet Inc.)
• Inventors: Greenberg, Don
• Primary Examiner(s): Salad, Abdullahi E
• Application Number:
  US15/997,393
• Time in Patent Office: 484 Days
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/5681 Pre-fetching or pre-delivering data based on network characteristics
• CPC Class Codes: H04L 67/63 Routing a service request depending on the request content or context

Abstract

This document describes a content delivery acceleration system including a communication interface configured to communicate with a remote device over a wireless network; a cache; and a controller configured to perform operations including: pre-computing one or more evaluation results for a webpage associated with a selectable network reference of a webpage, caching the one or more pre-computed evaluation results; retrieving, from the cache, the one or more pre-computed evaluation results; and pre-loading of one or more content tags for the one or more digital component slots, with the one or more content tags being preloaded with uniform resource locators (URLs) from which to load the digital components represented in the pre-computed evaluation results.

Claims

1. A content delivery acceleration system comprising:

a data storage; and

one or more processors configured to perform operations comprising;

computing one or more evaluation results for an online resource, with the one or more evaluation results each representing one or more digital components for presentation in the online resource, wherein computing the one or more evaluation results comprises;

generating parameters data using prior evaluation data; and

performing an evaluation for each of one or more digital component slots of the online resource based on the parameters data;

storing the one or more evaluation results in the data storage; and

responsive to receiving a request for the online resource from a system configured to serve the online resource;

loading one or more content tags associated with the online resource with one or more respective links, each link indicating a digital component of the one or more digital components represented in the one or more evaluation results.

2. The content delivery acceleration system of claim 1, wherein loading the one or more content tags comprises loading the one or more content tags with the one or more links in advance of receipt of a request from a remote system for one or more evaluation results.

3. The content delivery acceleration system of claim 1, wherein computing comprises computing the one or more evaluation results in advance of receipt of a request from a remote system for the one or more evaluation results.

4. The content delivery acceleration system of claim 1, the operations further comprising:

requesting, based on the one or more evaluation results, a digital component of the one or more digital components represented by the one or more evaluation results for presentation in the online resource;

receiving the digital component; and

loading the digital component for presentation in the online resource in advance of receiving a request for the online resource so that a latency in serving the online resource is reduced, relative to a latency in serving the online resource independent of loading the digital component in advance of receiving the request for the online resource.

5. The content delivery acceleration system of claim 4, wherein loading of the digital component enables the digital component and data of the online resource to be served together.

6. The content delivery acceleration system of claim 4, wherein the digital component comprises an advertisement.

7. The content delivery acceleration system of claim 1, wherein the online resource comprises a first online resource, and wherein the operations further comprise:

receiving resource data from a remote system, the resource data being for a second online resource and comprising one or more selectable network references to one or more third online resources and the first online resource;

parsing the received resource data for the one or more selectable network references; and

for a particular one of the one or more selectable network references, generating, based on the parsed online resource data, prediction data representing a likelihood that the particular one of the one or more selectable network references representing the first online resource is selected.

8. The content delivery acceleration system of claim 7, wherein generating the prediction data comprises:

receiving a user identifier and an identifier for the first online resource;

receiving data comprising one or more of user click data for the first online resource, resource data for the first online resource, and content provider data;

analyzing the received data using one or more machine-learning algorithms; and

returning a prediction value associated with a user for the first online resource, the prediction data comprising the prediction value.

9. The content delivery acceleration system of claim 7, wherein the online resource data for the second online resource comprises one or more search results based on a search query of a user, and wherein the one or more selectable network references comprise one or more clickable links to one or more additional online resources represented by the one or more search results.

10. The content delivery acceleration system of claim 7, wherein computing the one or more evaluation results comprises:

determining a threshold value for comparing the prediction data, the threshold value representing a specified likelihood the particular one of the one or more selectable network references is selected; and

comparing the threshold value to the prediction data for the particular one of the one or more selectable network references.

11. The content delivery acceleration system of claim 1, wherein the parameters data comprise real-time bidding (RTB) callout parameters.

12. The content delivery acceleration system of claim 1, the operations further comprising:

associating, with a user identifier, the one or more evaluation results representing the one or more digital component slots associated with the online resource;

storing the user identifier;

returning, in response to a request for the one or more evaluation results for the online resource from a user associated with the user identifier, the one or more evaluation results associated with the user identifier; and

deleting, from the data storage, the one or more evaluation results associated with the user identifier.

13. A method for content delivery acceleration comprising:

computing one or more evaluation results for an online resource, with the one or more evaluation results each representing one or more digital components for presentation in the online resource, wherein computing the one or more evaluation results comprises;

generating parameters data using prior evaluation data; and

performing an evaluation for each of one or more digital component slots of the online resource based on the parameters data;

storing the one or more evaluation results in a data storage; and

responsive to receiving a request for the online resource from a system configured to serve the online resource;

loading one or more content tags associated with the online resource with one or more respective links, each link indicating a digital component of the one or more digital components represented in the one or more evaluation results.

14. The method of claim 13, wherein loading the one or more content tags comprises loading the one or more content tags with the one or more links in advance of receipt of a request from a remote system for one or more evaluation results.

15. The method of claim 13, wherein computing comprises computing the one or more evaluation results in advance of receipt of a request from a remote system for the one or more evaluation results.

16. The method of claim 13, further comprising:

requesting, based on the one or more evaluation results, a digital component of the one or more digital components represented by the one or more evaluation results for presentation in the online resource;

receiving the digital component; and

loading the digital component for presentation in the online resource in advance of receiving a request for the online resource so that a latency in serving the online resource is reduced, relative to a latency in serving the online resource independent of loading the digital component in advance of receiving the request for the online resource.

17. The method of claim 16, wherein loading of the digital component enables the digital component and data of the online resource to be served together.

18. The method of claim 16, wherein the digital component comprises an advertisement.

19. The method of claim 13, wherein the online resource comprises a first online resource, and wherein the method further comprises:

receiving resource data from a remote system, the resource data being for a second online resource and comprising one or more selectable network references to one or more third online resources and the first online resource;

parsing the received resource data for the one or more selectable network references; and

for a particular one of the one or more selectable network references, generating, based on the parsed online resource data, prediction data representing a likelihood that the particular one of the one or more selectable network references representing the first online resource is selected.

20. The method of claim 19, wherein generating the prediction data comprises:

receiving a user identifier and an identifier for the first online resource;

receiving data comprising one or more of user click data for the first online resource, resource data for the first online resource, and content provider data;

analyzing the received data using one or more machine-learning algorithms; and

returning a prediction value associated with a user for the first online resource, the prediction data comprising the prediction value.

21. The method of claim 19, wherein the online resource data for the second online resource comprises one or more search results based on a search query of a user, and wherein the one or more selectable network references comprise one or more clickable links to one or more additional online resources represented by the one or more search results.

22. The method of claim 19, wherein computing the one or more evaluation results comprises:

determining a threshold value for comparing the prediction data, the threshold value representing a specified likelihood the particular one of the one or more selectable network references is selected; and

comparing the threshold value to the prediction data for the particular one of the one or more selectable network references.

23. The method of claim 19, wherein the parameters data comprise real-time bidding (RTB) callout parameters.

24. The method of claim 13, further comprising:

associating, with a user identifier, the one or more evaluation results representing the one or more digital component slots associated with the online resource;

storing the user identifier;

returning, in response to a request for the one or more evaluation results for the online resource from a user associated with the user identifier, the one or more evaluation results associated with the user identifier; and

deleting, from the data storage, the one or more evaluation results associated with the user identifier.

25. A non-transitory computer readable medium storing instructions that are executable by one or more processors configured to perform operations comprising:

computing one or more evaluation results for an online resource, with the one or more evaluation results each representing one or more digital components for presentation in the online resource, wherein computing the one or more evaluation results comprises;

generating parameters data using prior evaluation data; and

performing an evaluation for each of one or more digital component slots of the online resource based on the parameters data;

storing the one or more evaluation results in a data storage; and

responsive to receiving a request for the online resource from a system configured to serve the online resource;

loading one or more content tags associated with the online resource with one or more respective links, each link indicating a digital component of the one or more digital components represented in the one or more evaluation results.