CYBER FORAGING NETWORK SYSTEM FOR AUTOMATIC WIRELESS NETWORK ACCESS POINT DETECTION AND CONNECTION

• US 20150304920A1
• Filed: 01/17/2014
• Published: 10/22/2015
• Est. Priority Date: 01/18/2013
• Status: Active Grant

• Current Assignee: Forager Networks, Inc.
• Original Assignee: Forager Networks, Inc.
• Inventors: Cootey, Philip
• Granted Patent: US 9,609,560 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: H04W 28/18 Negotiating wireless communication parameters
• CPC Class Codes: H04W 36/08 Reselecting an access point
• CPC Class Codes: H04W 48/20 Selecting an access point
• CPC Class Codes: H04W 72/542 using measured or perceived quality

Abstract

A cyber-foraging network system which automatically and intelligently detects, selects, and connects to a wireless networking access point utilizing data obtained from its own environmental observations as well as from a robust wireless networking context aggregation/interpolation service.

Claims

1. A network system, comprising:

a plurality of wireless access points at a particular location or region;

a mobile wireless networking subsystem device having a cyber-foraging client application configured to collect environmental information data from the particular location or region including from the wireless access points;

a wireless networking context service subsystem in communication with the mobile wireless networking subsystem device, wherein the wireless networking context service subsystem receives the environmental information data from the mobile wireless networking subsystem device;

the wireless networking context service subsystem having a networking context aggregation module and a networking context interpolation module, the modules being operable to determine an optimal wireless access point for continuous connection with the mobile wireless networking subsystem based on the environmental information data; and

a controller configured to direct the mobile wireless networking subsystem to connect with the optimal wireless access point.

5. The network system of claim 1, wherein the environmental information data comprises network utilization data.

7. The network system of claim 1, wherein the environmental information data comprises metrics derived through application of one or more processing algorithms.

8. The network system of claim 1, wherein the environmental information data comprises detection, selection, and connection together forming an orthogonal state machine.

9. The network system of claim 1, wherein determination of optimal for the wireless access point is based on a quality of service (QoS) and a user preferred calibration.

10. The network system of claim 1, wherein determination of optimal for the wireless access point is based on network preferred calibration.

11. The network system of claim 1, wherein determination of optimal further comprises native physical and temporal factors including heading, geospatial velocity, security, security credentials, channel crowding, signal strength, signal strength relative to averaging window, prediction, suggestion, preferred networks, and upload/download velocity.

12. The network system of claim 1, wherein the aggregation module combines the environmental information data to form aggregated data.

2-4. -4. (canceled)

6. (canceled)

13-19. -19. (canceled)

20. A method of selecting an optimal wireless access point, comprising:

communicating with wireless access points at a particular location or region;

collecting environmental information data from the particular location or region including from the wireless access points;

aggregating the environmental information data for the wireless access points to produce aggregated data;

interpolating the aggregated data to produce interpolated data;

selecting the optimal wireless access point based on the interpolated data; and

communicating with the optimal wireless access point.

21. The method of claim 20, further comprising calibrating the interpolated data prior to selecting the optimal wireless access point.

22. The method of claim 20, wherein selecting the optimal wireless access point is based on a quality of service (QoS) and a specified calibration.

23. The method of claim 20, wherein selecting the optimal wireless access point further comprises native physical and temporal factors comprising heading, geospatial velocity, security, security credentials, channel crowding, signal strength, signal strength relative to averaging window, prediction, suggestion, preferred networks, and upload/download velocity.

24. The method of claim 20, further comprising weighting a quality of a signal from the wireless access points for selecting the optimal wireless access point.

25. The method of claim 20, wherein the environmental information data includes a cost of using each wireless access point.

26. The method of claim 25, further comprising selecting the optimal wireless access point based on a user'"'"'s maximum set cost for the wireless access points.

27. (canceled)

28. A mobile device, comprising:

a cyber-foraging client application configured to collect environmental information data from wireless access points, wherein the cyber-foraging client application sends the environmental information data to an external service for determination of an optimal wireless access point based on the environmental information data; and

a controller for directing the mobile device to connect to the optimal wireless access point.

33. The mobile device of claim 28, wherein the cyber-foraging client application further comprises a wireless networking context constructor.

36. The mobile device of claim 28, wherein the cyber-foraging client application further comprises a network handoff candidate selector.

37. The mobile device of claim 36, wherein the network handoff candidate selector selects the optimal wireless access point based on the optimal wireless access point signal while considering native physical and temporal factors.

38. The mobile device of claim 37, wherein the native physical and temporal factors include heading, geospatial velocity, security, channel crowding, signal strength, signal strength relative to averaging window, prediction, suggestion, and upload/download velocity.

39. The mobile device of claim 36, wherein the network handoff candidate selector comprises a policy control agent configured for weighting factors for selecting the optimal wireless access point signal.

41. The mobile device of claim 28, wherein the cyber-foraging client application further comprises a dynamic system calibrator configured to receive a cyber-foraging network system configuration set.

42. The mobile device of claim 41, wherein the dynamic system calibrator intersects with connection, selection, and detection together forming an orthogonal state machine.

43. The mobile device of claim 28, wherein the cyber-foraging client application further comprises a wireless networking context map generator for presenting wireless network context visualization.

44. The mobile device of claim 28, wherein the cyber-foraging client application further comprises a scan manager.

29. (canceled)

30. The mobile device of claim 2928, wherein the cyber-foraging client application further comprises an adaptable handoff strategy processor configured to receive interpolated data from the external service for determining an adaptable handoff strategy, and wherein the adaptable handoff strategy processor considers a connected velocity and/or a connected strength based on the received interpolated data for determining the adaptable handoff strategy.

31-32. -32. (canceled)

34-35. -35. (canceled)

40. (canceled)

45-55. -55. (canceled)