Performance-based content delivery

• US 9,769,248 B1
• Filed: 12/16/2014
• Issued: 09/19/2017
• Est. Priority Date: 12/16/2014
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Krishnan, Prasanth Krishnan Krishnasamy Navaneetha, Srinivasan, Vengadanathan, Tibrewal, Saharsh, Pandey, Rajeev Kumar
• Primary Examiner(s): MADAMBA, GLENFORD J
• Application Number:
  US14/572,705
• Time in Patent Office: 1,008 Days
• Field of Search: 709217
• CPC Class Codes: H04L 41/5067 Customer-centric QoS measurements
• CPC Class Codes: H04L 43/00 Arrangements for monitoring or testing data switching networks
• CPC Class Codes: H04L 43/087 Jitter
• CPC Class Codes: H04L 43/0876 Network utilisation, e.g. volume of load or congestion level
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/56 Provisioning of proxy services store-and-forward switching systems in data switching networks H04L12/54

Abstract

Systems and methods for performance-based content delivery are disclosed. A performance management service can define client performance categories based on performance data regarding content requesting, delivery and rendering, and thereby enable content providers to generate or update content based on characteristics of different performance categories in order to improve user experience. The performance management service may also predict performance categories for clients with respect to their currently submitted content requests based on applicable client classification criteria. The performance management service can provide the category prediction to content providers so that a version of the requested content appropriate for the predicted category is transmitted to the client.

Claims

1. A computer-implemented method for facilitating content delivery based on performance categories, the computer-implemented method comprising:

under control of a hardware computing device configured with specific computer executable instructions,

obtaining performance data from a plurality of client computing devices, wherein the performance data includes latency information regarding processing of requests for network resources submitted by individual client computing devices of the plurality of client computing devices over a specified period of time;

defining a plurality of performance categories based, at least in part, on an analysis of the performance data;

determining a performance characteristic that corresponds to a first performance category in the plurality of performance categories, wherein the performance characteristic identifies a characteristic of a subset of client computing devices in the plurality of client computing devices that belong to the first performance category;

transmitting a definition of the first performance category and the performance characteristic to a provider of network resources;

causing generation of at least one version of a target network resource by the provider based, at least in part, on the performance characteristic;

generating a prediction that a first client computing device in the plurality of client computing devices belongs to the first performance category, wherein the first client computing device transmitted a request to the provider for the target network resource;

transmitting, to the provider, the prediction; and

causing transmission of the at least one version of the target network resource, by the provider, to the first client computing device in response to the request for the target network resource based, at least in part, on the prediction.

2. The computer-implemented method of claim 1, wherein the performance data corresponds to requests for one or more types of network resource over the specified period of time.

3. The computer-implemented method of claim 1, wherein the analysis of the performance data comprises generating a sorted list of the plurality of client computing devices based, at least in part, on the latency information.

4. The computer-implemented method of claim 3, wherein determining the performance characteristic comprises determining at least one percentile associated with the sorted list of client computing devices.

5. The computer-implemented method of claim 1, wherein the performance characteristic corresponds to an aggregate statistic of latencies perceived by individual users associated with a respective client computing device of the subset of client computing devices for processing one or more network resources.

6. A computer-implemented method comprising:

under control of a hardware computing device configured with specific computer executable instructions,

defining a plurality of performance categories based, at least in part, on an analysis of performance data associated with requests for network resources submitted by a plurality of client computing devices;

determining a performance characteristic corresponding to a target performance category of the plurality of performance categories, wherein the performance characteristic identifies a characteristic of a subset of client computing devices in the plurality of client computing devices that belong to the target performance category;

causing generation of at least one version of a target network resource based, at least in part, on the performance characteristic and a definition of the target performance category;

generating a prediction that a first client computing device in the plurality of client computing devices belongs to the target performance category; and

causing transmission of the at least one version of the target network resource to the first client computing device in response to a request for the target network resource based, at least in part, on the prediction.

7. The computer-implemented method of claim 6, further comprising obtaining the performance data from at least one of the plurality of client computing devices or at least one computing device associated with a content provider that fulfills requests for network resources.

8. The computer-implemented method of claim 6, wherein defining the plurality of performance categories comprises defining the plurality of performance categories based, at least in part, on analysis of performance data associated with requests for similar network resources.

9. The computer-implemented method of claim 6, wherein defining the plurality of performance categories comprises defining the plurality of performance categories based, at least in part, on analysis of performance data associated with requests for network resources to similar content providers.

10. The computer-implemented method of claim 6, wherein causing generation of the at least one version of the target network resource comprises determining whether to include in-lining Cascading Style Sheets (CSS) or external CSS in the at least one version of the target network resource based, at least in part, on the performance characteristic.

11. A system comprising:

a data store configured to at least store computer-executable instructions; and

a hardware processor in communication with the data store, the hardware processor configured to execute the computer-executable instructions to at least;

define a plurality of performance categories based, at least in part, on an analysis of performance data associated with requests for network resources submitted by a plurality of client computing devices;

determine a performance characteristic corresponding to a target performance category of the plurality of performance categories, wherein the performance characteristic identifies a characteristic of a subset of client computing devices in the plurality of client computing devices that belong to the target performance category;

cause generation of at least one version of a target network resource based, at least in part, on the performance characteristic and a definition of the target performance category;

generate a prediction that a first client computing device in the plurality of client computing devices belongs to the target performance category; and

cause transmission of the at least one version of the target network resource to the first client computing device in response to a request for the target network resource based, at least in part, on the prediction.

12. The system of claim 11, wherein the performance data comprises at least one of process information, memory information, network data, resource data, or client computing component information.

13. The system of claim 11, wherein the analysis of the performance data comprises generating a sorted list of the plurality of client computing devices based, at least in part, on performance data associated with requests for similar network resources.

14. The system of claim 13, wherein defining the plurality of performance categories is based, at least in part, on a partition of the sorted list of the client computing devices.

15. The system of claim 11, wherein the performance characteristic corresponding to the target performance category includes at least one of latency information, size information, device information, or geographic information that are associated with the subset of client computing devices.

16. A non-transitory computer readable storage medium storing computer executable instructions that when executed by a processor perform operations comprising:

defining a plurality of performance categories based, at least in part, on an analysis of performance data associated with requests for network resources submitted by a plurality of client computing devices;

determining a performance characteristic corresponding to a target performance category of the plurality of performance categories, wherein the performance characteristic identifies a characteristic of a subset of client computing devices in the plurality of client computing devices that belong to the target performance category;

causing generation of at least one version of a target network resource based, at least in part, on the performance characteristic and a definition of the target performance category;

generating a prediction that a first client computing device in the plurality of client computing devices belongs to the target performance category; and

causing transmission of the at least one version of the target network resource to the first client computing device in response to a request for the target network resource based, at least in part, on the prediction.

17. The non-transitory computer-readable storage medium of claim 16, wherein the target performance category is defined based, at least in part, on an analysis of performance data associated with requests for the target network resource during a specified period of time.

18. The non-transitory computer-readable storage medium of claim 17, wherein the target performance category corresponds to one of a fast, medium, or slow performance category with respect to delivery of the target network resource to the plurality of client computing devices during the specified period of time.

19. The non-transitory computer-readable storage medium of claim 16, wherein causing generation of the at least one version of a target network resource includes causing generation of a first version of the target network resource, wherein the first version includes at least one of an in-lining Cascading Style Sheet (CSS), image of lower resolution, or simplified script code that corresponds to the target network resource.

20. The non-transitory computer-readable storage medium of claim 16, wherein causing generation of the at least one version of a target network resource includes causing generation of a second version of the target network resource, wherein the second version includes at least one of a reference to external Cascading Style Sheet (CSS), additional or enhanced image, or complicated script code that corresponds to the target network resource.