Mobile Access Point Detection

• US 20140036701A1
• Filed: 09/12/2012
• Published: 02/06/2014
• Est. Priority Date: 07/31/2012
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Gao, Weihua, Do, Ju-Yong, Zhang, Gengsheng, Bhatia, Ashok, Akgul, Ferit Ozan
• Granted Patent: US 9,167,551 B2
• Time in Patent Office: Days
• US Class Current: 370/252
• CPC Class Codes: H04W 24/00 Supervisory, monitoring or testing arrangements
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 48/16 Discovering, processing access restriction or access information
• CPC Class Codes: H04W 48/20 Selecting an access point
• CPC Class Codes: H04W 64/003 locating network equipment
• CPC Class Codes: H04W 84/005 Moving wireless networks
• CPC Class Codes: H04W 88/06 adapted for operation in multiple networks or having at least two operational modes, e.g. multi-mode terminals

Abstract

Methods and devices for detecting mobile access points are disclosed. In one embodiment, a method of detecting mobile access points comprises collecting crowdsourcing data associated with one or more access point devices, quantizing the crowdsourcing data to generate a quantized crowdsourcing data, for each access point device, determining an interfracile range of the access point device using the quantized crowdsourcing data, where the interfracile range is a measure of statistical dispersion of the quantized crowdsourcing data with respect to the access point device, identifying the access point device as a mobile access point device in response to the interfracile range exceeds a first predetermined range. The method of collecting crowdsourcing data comprises collecting the crowdsourcing data within a predetermined sliding time window.

Claims

1. A method of detecting mobile access points, comprising:

collecting crowdsourcing data associated with one or more access point devices;

quantizing the crowdsourcing data to generate a quantized crowdsourcing data;

for each access point device, determining an interfracile range of the access point device using the quantized crowdsourcing data, wherein the interfracile range is a measure of a statistical dispersion of the quantized crowdsourcing data with respect to the access point device; and

identifying the access point device as a mobile access point device in response to the interfracile range exceeds a first predetermined range.

2. The method of claim 1, wherein collecting crowdsourcing data comprises:

collecting the crowdsourcing data in accordance with timer based observations;

collecting the crowdsourcing data in accordance with an opportunistic data collection of WiFi scans by mobile clients; and

collecting the crowdsourcing data in accordance with a failure based data collection of wireless local area network (WLAN) scans by the mobile clients.

3. The method of claim 1, wherein collecting crowdsourcing data further comprises:

collecting the crowdsourcing data in accordance with a maximum number of observations to be uploaded within a period between uploads;

collecting the crowdsourcing data in accordance with the maximum number of observations to be uploaded in an upload; and

collecting the crowdsourcing data in accordance with horizontal estimated position error values of the access point device.

4. The method of claim 1, wherein collecting crowdsourcing data further comprises:

collecting the crowdsourcing data within a predetermined sliding time window.

5. The method of claim 1, wherein quantizing crowdsourcing data comprises:

quantizing the crowdsourcing data in accordance with a predefined time segment;

quantizing the crowdsourcing data in accordance with predefined horizontal estimated position error values of the access point device; and

quantizing the crowdsourcing data in accordance with predefined media access control addresses.

6. The method of claim 1, wherein the interfracile range comprises at least one of latitude range and longitude range of the access point device.

7. The method of claim 1, wherein the statistical dispersion comprises a predetermined upper range and a predetermined lower range.

8. The method of claim 1 further comprises:

determining a plurality of mobile uploads associated with the access point device using the quantized crowdsourcing data;

determining a position of the access point device using the plurality of mobile uploads;

comparing the position of the access point device to a previous position of the access point device; and

identifying the access point device as the mobile access point device in response to the position of the access point device has moved over a second predetermined range.

9. The method of claim 1 further comprises:

storing information associated with the mobile access point device in a database; and

using information stored in the database in subsequent detection of the mobile access point device.

10. A computer program product comprising a non-transitory medium storing computer programs for execution by one or more computer systems, the computer program product comprising:

code for collecting crowdsourcing data associated with one or more access point devices;

code for quantizing the crowdsourcing data to generate a quantized crowdsourcing data;

for each access point device, code for determining an interfracile range of the access point device using the quantized crowdsourcing data, wherein the interfracile range is a measure of a statistical dispersion of the quantized crowdsourcing data with respect to the access point device; and

code for identifying the access point device as a mobile access point device in response to the interfracile range exceeds a first predetermined range.

11. The computer program product of claim 10, wherein code for collecting crowdsourcing data comprises:

code for collecting the crowdsourcing data in accordance with timer based observations;

code for collecting the crowdsourcing data in accordance with an opportunistic data collection of WiFi scans by mobile clients; and

code for collecting the crowdsourcing data in accordance with a failure based data collection of wireless local area network (WLAN) scans by the mobile clients.

12. The computer program product of claim 10, wherein code for collecting crowdsourcing data further comprises:

code for collecting the crowdsourcing data in accordance with a maximum number of observations to be uploaded within a period between uploads;

code for collecting the crowdsourcing data in accordance with the maximum number of observations to be uploaded in an upload; and

code for collecting the crowdsourcing data in accordance with horizontal estimated position error values of the access point device.

13. The computer program product of claim 10, wherein code for collecting crowdsourcing data further comprises:

code for collecting the crowdsourcing data within a predetermined sliding time window.

14. The computer program product of claim 10, wherein code for quantizing crowdsourcing data comprises:

code for quantizing the crowdsourcing data in accordance with a predefined time segment;

code for quantizing the crowdsourcing data in accordance with predefined horizontal estimated position error values of the access point device; and

code for quantizing the crowdsourcing data in accordance with predefined media access control addresses.

15. The computer program product of claim 10, wherein the interfracile range comprises at least one of latitude range and longitude range of the access point device.

16. The computer program product of claim 10, wherein the statistical dispersion comprises a predetermined upper range and a predetermined lower range.

17. The computer program product of claim 10 further comprises:

code for determining a plurality of mobile uploads associated with the access point device using the quantized crowdsourcing data;

code for determining a position of the access point device using the plurality of mobile uploads;

code for comparing the position of the access point device to a previous position of the access point device; and

code for identifying the access point device as the mobile access point device in response to the position of the access point device has moved over a second predetermined range.

18. The computer program product of claim 10 further comprises:

code for storing information associated with the mobile access point device in a database; and

code for using information stored in the database in subsequent detection of the mobile access point device.

19. An apparatus, comprising:

at least one processor;

a crowdsourcing data manager and a data aggregation module configured to work with the at least one processor, wherein

the crowdsourcing data manager comprises logic configured to collect crowdsourcing data associated with one or more access point devices;

the data aggregation module comprises logic configured to quantize the crowdsourcing data to generate a quantized crowdsourcing data;

for each access point device, determining an interfracile range of the access point device using the quantized crowdsourcing data, wherein the interfracile range is a measure of a statistical dispersion of the quantized crowdsourcing data with respect to the access point device; and

identifying the access point device as a mobile access point device in response to the interfracile range exceeds a first predetermined range.

20. The apparatus of claim 19, wherein logic configured to collect crowdsourcing data comprises:

logic configured to collect the crowdsourcing data in accordance with timer based observations;

logic configured to collect the crowdsourcing data in accordance with an opportunistic data collection of WiFi scans by mobile clients; and

logic configured to collect the crowdsourcing data in accordance with a failure based data collection of wireless local area network (WLAN) scans by the mobile clients.

21. The apparatus of claim 19, wherein logic configured to collect crowdsourcing data further comprises:

logic configured to collect the crowdsourcing data in accordance with a maximum number of observations to be uploaded within a period between uploads;

logic configured to collect the crowdsourcing data in accordance with the maximum number of observations to be uploaded in an upload; and

logic configured to collect the crowdsourcing data in accordance with horizontal estimated position error values of the access point device.

22. The apparatus of claim 19, wherein logic configured to collect crowdsourcing data further comprises:

logic configured to collect the crowdsourcing data within a predetermined sliding time window.

23. The apparatus of claim 19, wherein logic configured to quantize crowdsourcing data comprises:

logic configured to quantize the crowdsourcing data in accordance with a predefined time segment;

logic configured to quantize the crowdsourcing data in accordance with predefined horizontal estimated position error values of the access point device; and

logic configured to quantize the crowdsourcing data in accordance with predefined media access control addresses.

24. The apparatus of claim 19, wherein the interfracile range comprises at least one of latitude range and longitude range of the access point device.

25. The apparatus of claim 19, wherein the statistical dispersion comprises a predetermined upper range and a predetermined lower range.

26. The apparatus of claim 19 further comprises:

logic configured to determine a plurality of mobile uploads associated with the access point device using the quantized crowdsourcing data;

logic configured to determine a position of the access point device using the plurality of mobile uploads;

logic configured to compare the position of the access point device to a previous position of the access point device; and

logic configured to identify the access point device as the mobile access point device in response to the position of the access point device has moved over a second predetermined range.

27. The apparatus of claim 19 further comprises:

logic configured to store information associated with the mobile access point device in a database; and

logic configured to use information stored in the database in subsequent detection of the mobile access point device.

28. An apparatus, comprising:

means for collecting crowdsourcing data associated with one or more access point devices;

means for quantizing the crowdsourcing data to generate a quantized crowdsourcing data;

for each access point device, means for determining an interfracile range of the access point device using the quantized crowdsourcing data, wherein the interfracile range is a measure of a statistical dispersion of the quantized crowdsourcing data with respect to the access point device; and

means for identifying the access point device as a mobile access point device in response to the interfracile range exceeds a first predetermined range.

29. The apparatus of claim 28, wherein means for collecting crowdsourcing data further comprises:

means for collecting the crowdsourcing data within a predetermined sliding time window.

30. The apparatus of claim 28, wherein means for quantizing crowdsourcing data comprises:

means for quantizing the crowdsourcing data in accordance with a predefined time segment;

means for quantizing the crowdsourcing data in accordance with predefined horizontal estimated position error values of the access point device; and

means for quantizing the crowdsourcing data in accordance with predefined media access control addresses.

31. The apparatus of claim 28 further comprises:

means for determining a plurality of mobile uploads associated with the access point device using the quantized crowdsourcing data;

means for determining a position of the access point device using the plurality of mobile uploads;

means for comparing the position of the access point device to a previous position of the access point device; and

means for identifying the access point device as the mobile access point device in response to the position of the access point device has moved over a second predetermined range.

32. The apparatus of claim 28 further comprises:

means for storing information associated with the mobile access point device in a database; and

means for using information stored in the database in subsequent detection of the mobile access point device.