System and method for pushing data to a mobile device

• US 20050108322A1
• Filed: 03/11/2003
• Published: 05/19/2005
• Est. Priority Date: 03/11/2002
• Status: Abandoned Application

• Current Assignee: Malikie Innovations Limited (Key Patent Innovations Limited)
• Original Assignee: Michael Shenfield, Robert Kline
• Inventors: Shenfield, Michael, Kline, Robert
• Application Number:
  US10/507,083
• Publication Number:
  US 20050108322A1
• Time in Patent Office: Days
• US Class Current: 709/203
• CPC Class Codes: G06F 16/9574 of access to content, e.g. by caching
• CPC Class Codes: H04L 67/04 specially adapted for terminals or networks with limited capabilities; specially adapted for terminal portability
• CPC Class Codes: H04L 67/55 Push-based network services
• CPC Class Codes: H04L 69/329 in the application layer [OSI layer 7]

Abstract

A system for handling information requests from mobile devices (100) includes a memory (1100), a state prediction module (1200), and a push module (1300). The memory (1100) is operable to store data requests received from the mobile devices (100). The state prediction module (1200) is operable to access the memory (1100) to predict forecasted data requests for a mobile device (100) based on the stored data requests. The push module (1300) is operable to receive the forecasted data requests from the state prediction module (1200) and in response request and receive response data related to the forecasted data requests and prepare the response data for transmission to the mobile device (100) over a wireless network (105).

Claims

1. A system for handling data requests from mobile devices, the system comprising:

a memory operable to store data requests received from at least one mobile device;

a state prediction module operable to access the memory and predict a first forecasted data request for a mobile device based on the stored data requests; and

a push module operable to receive the first forecasted data request from the state prediction module and in response request and receive first response data related to the first forecasted data request and prepare the first response data for transmission to the mobile device over a wireless network.

2. The system of claim 1, wherein the first forecasted data request is predicted in response to receiving a data request from the mobile device.

3. The system of claim 2, wherein the state prediction module is further operable to generate prediction data based on the stored date requests, and to update the prediction data based on the reception of a prediction notification received from the mobile device in response to the first response data.

4. The system of claim 1, wherein the state prediction module is further operable to predict the first forecasted data request independent of a data request received from the mobile device.

5. The system of claim 4, wherein:

the state prediction module is further operable to receive a data request from the mobile device and in response access the memory and predict a second forecasted data request based on the received data request and the stored data requests; and

the push module is further operable to receive the received data request and the second forecasted data request from the state prediction module and in response request and receive second response data related to the received data request and the second forecasted data request and prepare the second response data for transmission to the mobile device over a wireless network.

6. The system of claim 4, wherein the state prediction module is further operable to predict the first forecasted data request on a periodic basis.

7. The system of claim 5, wherein the state prediction module is further operable to select prediction modes according to the identified subset of stored data.

8. The system of claim 7, wherein the prediction modes comprise:

an atomic mode that operates on stored data requests specific to the identity of the mobile device; and

a group mode that operates on stored data requests specific to a plurality of mobile devices.

9. The system of claim 5, wherein the state prediction module comprises a Markov chain module operable to predict the first and second forecasted data requests.

10. The system of claim 5, wherein the second forecasted data request comprises a set of consecutive data requests and consecutive response data referenced from the received data request.

11. A computer implemented method for handling date requests from mobile devices, the method comprising:

receiving and storing data requests received from the mobile devices;

comparing a received data request from a mobile device to prediction data to predict forecasted data requests based on the comparison;

requesting and receiving response data related to the received data request and the forecasted data requests; and

preparing the response data for transmission to the mobile device over wireless network.

12. The method of claim 11, further comprising the steps of:

identifying the mobile device from the data request;

identifying a subset of prediction data based on the identity of the mobile device; and

comparing the subset of stored data requests to the received data request to predict the forecasted data requests.

13. The method of claim 12, further comprising the steps of:

assigning a probability value to the forecasted data requests;

comparing the probability value to a threshold;

if the probability value does not exceed the threshold, then;

expanding the subset of prediction data to include data requests from other mobile devices; and

predicting further forecasted data requests based on the expanded prediction data.

14. The method of claim 11, wherein the step at comparing a received data request from a mobile device to prediction data to predict forecasted data requests based on the comparison comprises the steps of:

selecting a set of states having a transition probability from a current mobile device state greater than a selection probability threshold;

incrementing the set of states until the set of states transition probability from the current mobile device state is less than the selection probability threshold.

15. The method of claim 14, wherein the step of comparing a received data request from a mobile device to prediction data to predict forecasted data requests based on the comparison further comprises the steps of:

determining a cardinality of the set of states;

comparing the cardinality of the set of states to a maximum depth;

if the cardinality of the set of states exceeds the maximum depth, then adjusting the set of states.

16. The method of claim 15, wherein the step of adjusting the set of states comprises:

limiting the set of states to the maximum depth; and

selecting a subset of the set of states such that the transition probability from the current mobile device state is maximized.

17. The method of claim 14, further comprising the step of incrementing the selection probability threshold after each increment to the set of states.

18. The method of claim 11, further comprising the step of predicting an independent forecasted data request for a mobile device independent of a data request received from the mobile device.

19. The system of claim 18, further comprising the step of receiving a successful prediction notification from the mobile device and updating the prediction data based on the successful prediction notification.

20. The system of claim 18, wherein the step of predicting an independent forecasted data request is performed on a periodic basis.