Weighted request rate limiting for resources

• US 9,058,210 B2
• Filed: 11/17/2010
• Issued: 06/16/2015
• Est. Priority Date: 03/23/2010
• Status: Active Grant

• Current Assignee: PayPal, Inc. (PayPal Holdings, Inc.)
• Original Assignee: eBay Inc.
• Inventors: Avalani, Bhaven, Kumar, Abhinav, Murphy, Ronald Francis, Zhao, Ping
• Primary Examiner(s): Winder, Patrice
• Assistant Examiner(s): Chang, Julian
• Application Number:
  US12/948,599
• Publication Number:
  US 20110238838A1
• Time in Patent Office: 1,672 Days
• Field of Search: 709201-203, 709217-219, 709223-235, 726 22- 25
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3331 Query processing
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 2209/504 Resource capping
• CPC Class Codes: G06F 9/5011 the resources being hardware resources other than CPUs, Servers and Terminals
• CPC Class Codes: G06F 9/505 considering the load
• CPC Class Codes: H04L 47/70 Admission control; Resource allocation
• CPC Class Codes: H04L 63/10 for controlling access to devices or network resources
• 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: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

Methods and systems to automatically respond to consider the weight of a request when responding to requests associated with resources are described. In one embodiment, an interface module may be configured to receive a request associated with consumer identifier and a resource. A calculator module may be configured to determine a weight of the request and a usage module configured to calculate, using a processor, a usage level associated with the consumer identifier, the usage level based on a usage history associated with the consumer identifier. An enforcer module may also be configured to respond to the request based on the usage level and the weight of the request. In one embodiment, the usage module may also be configured to update the usage level associated with the consumer identifier based on the weight of the request.

Claims

1. A method comprising:

receiving a search request associated with a consumer identifier and a search term;

determining a predicted weight of the search request based at least on the search term;

updating a usage history corresponding to the consumer identifier, based on the predicted weight of the search request and an actual weight of the search request;

calculating, using a processor, a usage level associated with the consumer identifier, the usage level based on a pattern identified in the usage history associated with the consumer identifier; and

responding to the search request based on the usage level and the predicted weight of the search request in accordance with a usage policy.

2. The method of claim 1, wherein the predicted weight of the search request is determined based on at least one of a type of the search request and parameters associated with the search request.

3. The method of claim 1, wherein the usage policy is based on a change in response time associated with the consumer identifier over a time period.

4. The method of claim 1, wherein responding to the search request comprises rejecting the request.

5. The method of claim 1, further comprising updating the usage level associated with the consumer identifier based on an actual weight of the search request.

6. The method of claim 1, wherein the request comprises the consumer identifier and a resource identifier.

17. The method of claim 1, wherein the updating of the usage history corresponding to the consumer identifier is further based on a response time, a request type, and a request parameter.

7. A system comprising one or more modules implemented by one or more processors and configured to:

receive a search request associated with a consumer identifier and a search term;

determine a predicted weight of the search request based at least in part on the search term;

update a usage history corresponding to the consumer identifier, based on the predicted weight of the search request and an actual weight of the search request;

calculate a usage level associated with the consumer identifier, the usage level based on a pattern identified in the usage history associated with the consumer identifier; and

respond to the request based on the usage level and the predicted weight of the search request in accordance with a usage policy.

8. The system of claim 7, wherein the usage policy is based on a change in response time associated with the consumer identifier over a time period.

9. The system of claim 7, wherein the enforcer module is further configured to reject the search request.

10. The system of claim 7, wherein the usage module is further configured to update the usage level associated with the consumer identifier based on an actual weight of the search request.

11. The system of claim 7, wherein the search request comprises the consumer identifier and a resource identifier.

18. The system of claim 7, wherein the updating of the usage history corresponding to the consumer identifier is further based on a response time, a request type, and a request parameter.

12. A non-transitory machine-readable medium comprising stored instructions, wherein the instructions, when executed, cause a machine to perform operations, comprising:

receiving a search request associated with a consumer identifier and a search term;

determining a predicted weight of the search request based at least in part on the search term;

updating a usage history corresponding to the consumer identifier, based on the predicted weight of the search request and an actual weight of the search request;

calculating a usage level associated with the consumer identifier, the usage level based on a pattern identified in the usage history associated with the consumer identifier; and

responding to the search request based on the usage level and the predicted weight in accordance with a usage policy.

13. The non-transitory machine-readable medium of claim 12, wherein the predicted weight of the search request is based on responding to a plurality of previous search requests.

14. The non-transitory machine-readable medium of claim 12, the machine-readable medium further comprising stored instructions, wherein the instructions, when executed, cause a machine to update the usage history associated with the consumer identifier based on the search request.

19. The non-transitory machine-readable medium of claim 12, wherein the updating of the usage history corresponding to the consumer identifier is further based on a response time, a request type, and a request parameter.

15. A system, comprising:

means for receiving a search request associated with a consumer identifier and a search term;

means for determining a predicted weight of the search request, based at least in part on the search term;

means for updating a usage history corresponding to the consumer identifier, based on the predicted weight of the search request and an actual weight of the search request;

means for calculating, using a processor, a usage level associated with the consumer identifier, the usage level based on a pattern identified in the usage history associated with the consumer identifier; and

means for responding to the search request based on the predicted weight of the search request and the first usage level in accordance with a usage policy.

16. The system of claim 15, further comprising:

means for updating the usage history associated with the consumer identifier based on the search request.

20. The system of claim 15, wherein the means for updating the usage history corresponding to the consumer identifier updates the usage history corresponding to the consumer identifier based on a response time, a request type, and a request parameter.