METHOD OF REDUCING RESPONSE TIME FOR DELIVERY OF VEHICLE TELEMATICS SERVICES

• US 20110145507A1
• Filed: 12/10/2009
• Published: 06/16/2011
• Est. Priority Date: 12/10/2009
• Status: Active Grant

• Current Assignee: General Motors LLC (General Motors Company)
• Original Assignee: General Motors LLC (General Motors Company)
• Inventors: Ramamurthy, Kannan, Sidhu, Navjot
• Granted Patent: US 8,732,405 B2
• Time in Patent Office: Days
• US Class Current: 711/137
• CPC Class Codes: G06Q 10/00 Administration; Management

Abstract

A method of operating a predictive data cache includes receiving a request for telematics service from a telematics service requester, determining the subject matter of the request, querying a predictive data cache to determine if the predictive data cache includes a service response to the subject matter of the request and, if the predictive data cache includes the service response, then providing the service response to the requester and updating the predictive data cache using the subject matter of the request. The subject matter can include one or more of: an event description, an event period, or an event location based on the request.

Claims

1. A method of operating a predictive data cache, the steps comprising:

(a) receiving a request for telematics service from a telematics service requester;

(b) determining the subject matter of the request, the subject matter comprising one or more of;

an event description, an event period, or an event location based on the request;

(c) querying a predictive data cache to determine if the predictive data cache includes a service response to the subject matter of the request;

(d) if the predictive data cache includes the service response, providing the service response to the requester; and

(e) updating the predictive data cache using the subject matter of the request.

2. The method of claim 1, wherein step (c) further comprises comparing at least one variable of the subject matter of the request for telematics service with subject matter previously stored in the predictive data cache.

3. The method of claim 1, wherein the event description further comprises the name of a public or private social gathering.

4. The method of claim 1, wherein the subject matter of the request further comprises a priority value associated with the request.

5. The method of claim 1, wherein each request stored in the predictive data cache includes a priority value.

6. The method of claim 1, wherein step (e) further comprises adding or subtracting requests or service responses to or from the predictive data cache based on the probability the requests will occur in the future.

7. The method of claim 6, further comprising calculating the probability that a telematics request occurs using a Poisson model.

8. The method of claim 1, wherein step (e) further comprises identifying a predetermined number of ranked requests to add to the predictive data cache and removing a previously stored number of ranked requests.

9. A method of operating a predictive data cache, the steps comprising:

(a) receiving a request for telematics service;

(b) determining the subject matter of the request;

(c) storing the subject matter of the request in a database;

(d) attaching a probability value to the request based on the subject matter;

(e) ranking the request relative to other previously-received requests stored in the database based on the probability values;

(f) identifying a predetermined number of the most-frequently-occurring ranked requests;

(g) generating one or more service responses to the identified requests; and

(h) uploading the request and service responses to a predictive data cache.

10. The method of claim 9, wherein the subject matter further comprises one or more of:

an event description, an event period, or an event location based on the request.

11. The method of claim 10, wherein the event description further comprises the name of a public or private social gathering.

12. The method of claim 9, wherein the subject matter of the request further comprises a priority value associated with the request.

13. The method of claim 9, wherein each request stored in the predictive data cache includes a priority value.

14. The method of claim 9, further comprising the step of adding or subtracting requests or service responses to or from the predictive data cache based on the probability values.

15. The method of claim 9, further comprising the probability that a telematics request occurs using a Poisson model.

16. A method of operating a predictive data cache, the steps comprising:

(a) receiving a request for telematics service that identifies the location of the telematics service requester;

(b) determining an event based on the request;

(c) determining a temporal range based on the event;

(d) determining if the request, the event, or the temporal range exists in a predictive data cache and if so, then;

(i) accessing a service response based on the request, wherein the service response is stored in the predictive data cache;

(ii) delivering the service response to the telematics service requester;

(e) comparing the request for telematics service, the event, and the temporal range with requests for telematics service, events, and temporal ranges previously stored in a database;

(f) ranking the request for telematics service, the determined event, and the determined temporal range based on a frequency of occurrence, probability of occurrence, or priority with respect to the requests for telematics service, events, and temporal ranges previously stored in the database;

(g) identifying a predetermined number of ranked requests, determined events, or determined temporal ranges; and

(h) updating the predictive data cache with the identified ranked requests.

17. The method of claim 16, wherein the request further comprises a priority value associated with the request.

18. The method of claim 16, wherein each request stored in the predictive data cache includes a priority value.

19. The method of claim 16, further comprising calculating the probability that a telematics request occurs using a Poisson model.

20. The method of claim 16, wherein step (h) further comprises removing a previously stored predetermined number of ranked requests, determined events, or determined temporal ranges.