Automated service interface optimization

• US 9,906,622 B2
• Filed: 07/26/2016
• Issued: 02/27/2018
• Est. Priority Date: 12/17/2009
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Jenkins, Jonathan A., Sehn, Timothy M., Maher, Brian Evan
• Primary Examiner(s): Ho, Andy
• Application Number:
  US15/219,577
• Publication Number:
  US 20160337469A1
• Time in Patent Office: 581 Days
• Field of Search: 719316, 719328
• CPC Class Codes: G06F 16/1734 Details of monitoring file system events, e.g. by the use of hooks, filter drivers, logs
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 2209/541 Client-server
• CPC Class Codes: G06F 9/54 Interprogram communication
• CPC Class Codes: H04L 43/08 Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
• CPC Class Codes: H04L 47/10 Flow control; Congestion control
• CPC Class Codes: H04L 47/782 Hierarchical allocation of resources, e.g. involving a hierarchy of local and centralised entities
• CPC Class Codes: H04L 47/808 User-type aware
• CPC Class Codes: H04L 67/01 Protocols
• CPC Class Codes: H04L 67/60 Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources admission control or resource allocation H04L47/70

Abstract

Disclosed are various embodiments for automated service interface optimization. In one embodiment, usage metrics are determined for a service client corresponding to usage of a set of data items within a data object. An optimized data object is provided to the service client in response to a request from the service client for the data object. The optimized data object includes empty values in place of one or more data items in the set of data items. The data item(s) are determined based at least in part on the usage metrics.

Claims

1. A system, comprising:

at least one computing device; and

at least one application executable in the at least one computing device, wherein when executed the at least one application causes the at least one computing device to at least;

determine a plurality of usage metrics for a service client corresponding to usage of a set of data items within a data object; and

provide an optimized data object to the service client in response to a request from the service client for the data object, the optimized data object including at least one empty value in place of at least one data item in the set of data items, the at least one data item being determined based at least in part on the plurality of usage metrics.

2. The system of claim 1, wherein the request from the service client for the data object includes a filtering parameter indicating that the at least one data item is to be excluded from the optimized data object.

3. The system of claim 1, wherein the optimized data object includes a data item from another data object that is aggregated with the data object based at least in part on the plurality of usage metrics.

4. The system of claim 1, wherein the plurality of usage metrics include usage by another service client of the set of data items within the data object.

5. The system of claim 1, wherein when executed the at least one application further causes the at least one computing device to at least predict that the service client will not access the at least one data item based at least in part on the plurality of usage metrics.

6. The system of claim 1, wherein the optimized data object includes at least one accessor used to access respective data values for the at least one data item.

7. The system of claim 1, wherein the optimized data object is of a different type than the data object.

8. The system of claim 1, wherein a data size of the optimized data object is smaller than a data size of the data object.

9. The system of claim 1, wherein a data encoding complexity of the optimized data object is lower than a data encoding complexity of the data object.

10. A method, comprising:

receiving, via one or more computing devices, a request from a service client for a data object, the request being associated with a filtering parameter indicating at least one data item normally in the data object that should be excluded from the data object; and

providing, via the one or more computing devices, an optimized data object to the service client in response to the request, wherein the at least one data item is excluded based at least in part on the filtering parameter.

11. The method of claim 10, further comprising configuring, via the one or more computing devices, the service client to provide the filtering parameter in the request.

12. The method of claim 10, further comprising receiving, via the one or more computing devices, the filtering parameter from a provider framework application based at least in part on an identification of the service client.

13. The method of claim 10, wherein the optimized data object includes at least one empty value in place of the at least one data item.

14. The method of claim 10, wherein the optimized data object excludes at least one accessor used to access the at least one data item in the data object.

15. A method, comprising:

determining, via one or more computing devices, a plurality of usage metrics for a service client corresponding to usage of respective sets of data items within individual ones of a plurality of data objects; and

providing, via the one or more computing devices, an optimized data object to the service client in response to a request from the service client for a particular data object of the plurality of data objects, the optimized data object including an aggregation of data items from a plurality of the respective sets of data items, the aggregation of data items being selected based at least in part on the plurality of usage metrics.

16. The method of claim 15, wherein the aggregation of data items includes fewer than all data items from the plurality of the respective sets of data items.

17. The method of claim 15, wherein the aggregation of data items excludes at least one data item from the particular data object.

18. The method of claim 15, wherein the optimized data object includes at least one empty value in place of at least one data item from the particular data object.

19. The method of claim 15, further comprising determining, via the one or more computing devices, that the service client is likely to use all data items in the aggregation of data items.

20. The method of claim 15, further comprising storing, via the one or more computing devices, the request from the service client for the particular object in a cache buffer along with a request from the service client for another data object of the plurality of data objects.