MODELING NETWORK SIGNALING IN A MOBILE NETWORK

• US 20150012257A1
• Filed: 06/03/2014
• Published: 01/08/2015
• Est. Priority Date: 07/02/2013
• Status: Active Grant

• Current Assignee: Seven Networks LLC (SoftBank Group Corp.)
• Original Assignee: Seven Networks Inc
• Inventors: Backholm, Ari, Shvayka, Andrey
• Granted Patent: US 9,819,552 B2
• Time in Patent Office: Days
• US Class Current: 703/13
• CPC Class Codes: H04L 41/0893 Assignment of logical groups to network elements
• CPC Class Codes: H04L 41/0894 Policy-based network configuration management
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 43/10 Active monitoring, e.g. heartbeat, ping or trace-route

Abstract

The disclosed technology includes systems and methods for modeling signaling and/or connections in a mobile network, and specifically, the benefits of any optimization technique on the traffic including signals and/or connections in the mobile network. Embodiments can allocate signaling to specific applications (e.g., to determine which applications are chatty and which can cause problematic signaling), and/or to further model the optimizations or savings utilizing the disclosed traffic optimization technology. In some embodiments, to enable or enhance the performance of the data traffic and signal optimization for the network, the disclosed technology includes one or more fields (e.g., an expanded “CRCS” fields) that are calculated by, for example, a CRCS analysis core module, to define and identify at least: (1) whether a transaction causes a connection (and thus signaling); and (2) the number of connections that are reduced or saved by the disclosed embodiments of distributed caching and proxy system.

Claims

1. A method of modeling signaling in a mobile network, the method comprising:

determining if transactions initiated by mobile applications executing on a mobile device in the mobile network cause network signaling requiring a corresponding radio connection,

wherein at least a portion of the network signaling caused by the transactions is filtered by a traffic optimization engine; and

modeling the network signaling for the mobile device based, at least in part, on the filtered network signaling.

2. The method of claim 1, wherein the filtered network signaling does not cause a corresponding radio connection.

3. The method of claim 1, wherein modeling the network signaling for the mobile device further comprises calculating signaling efficiency indicating a total number of the radio connections that are saved as a result of the filtering.

4. The method of claim 3, wherein calculating the signaling efficiency further comprises:

accessing a radio log and a traffic activity log associated with the mobile device;

modeling a quantity of virtual radio connections based on the radio log and the traffic activity log,

wherein the virtual radio connections indicate radio connections that would occur but for said filtering;

determining a quantity of actual radio connections based on the radio log,

wherein the total number of the radio connections that are saved comprises the difference between the quantity of virtual radio connections and the quantity of actual radio connections.

5. The method of claim 1, wherein modeling the network signaling for the mobile device further comprises calculating a time connected efficiency indicating a total radio connection time saved as a result of the filtering.

6. The method of claim 5, wherein calculating the time connected efficiency further comprises:

accessing a radio log and a traffic activity log associated with the mobile device;

modeling a virtual radio time connected based on the radio log and the traffic activity log,

wherein the virtual radio time connected indicates an amount of time that the mobile device radio would be active but for said filtering;

determining an actual radio time connected based on the radio log,

wherein the actual radio time connected indicates an amount of time that the mobile device radio is active;

wherein the total radio connection time saved comprises the difference between the virtual radio time connected and the actual radio time connected.

7. The method of claim 1, further comprising:

tracking the transactions initiated by the mobile applications executing on the mobile device in the mobile network.

8. The method of claim 1, further comprising:

applying, by the traffic optimization engine, a traffic optimization technique to filter the network signaling such that at least the portion of the network signaling is filtered.

9. The method of claim 1, further comprising:

accessing traffic activity logs indicating traffic metrics measured at multiple traffic measurement points in the mobile device,

wherein modeling the network signaling further comprises calculating a connection status and a time connected interval based on the traffic metrics.

10. The method of claim 1, wherein modeling the network signaling for the mobile device further comprises attributing the network signaling to individual applications of the mobile applications executing on the mobile device.

11. The method of claim 1, further comprising:

accessing a radio log and a traffic activity log associated with the mobile device,

wherein the radio log indicates a state of a mobile device radio,

wherein the traffic activity log indicates various traffic metrics measured at multiple measurement points in the mobile device; and

maintaining the traffic activity log by calculating one or more CRCS fields.

12. The method of claim 11, wherein modeling the network signaling based on the one or more CRCS fields.

13. The method of claim 11, wherein maintaining the traffic activity log comprises long polling.

14. The method of claim 11, wherein the one or more CRCS fields are divided into connection flag fields and time connected count fields.

15. The method of claim 11, wherein the one or more CRCS fields are categorized into one or more of the following categories:

actual, simulated, actual simulated, virtual simulated, actual simulated per application, and virtual simulated per application.

16. The method of claim 1, wherein the traffic optimization engine comprises one or more elements of a distributed caching and proxy system.

17. The method of claim 16, wherein the distributed caching and proxy system includes a proxy client and a proxy server.

18. The method of claim 17, wherein the filtered radio connections are cached locally by the proxy client.

19. A method of modeling network signaling in a mobile network, the method comprising:

accessing a radio log associated with a mobile device operating in the mobile network, the radio log indicating a state of a mobile device radio;

accessing a traffic activity log associated with the mobile device, the traffic activity log indicating various traffic metrics measured at multiple measurement points in the mobile device;

calculating one or more CRCS fields based on one or more of the radio log and the traffic activity log; and

modeling the network signaling for the mobile device based on the one or more CRCS fields.

20. The method of claim 19, further comprising:

determining if transactions initiated by mobile applications executing on the mobile device in the mobile network cause network signaling requiring a corresponding radio connection on the mobile device,

wherein at least a portion of the network signaling caused by the transactions is filtered by a traffic optimization engine.

21. The method of claim 19, wherein the filtered network signaling does not cause a corresponding radio connection on the mobile device and the unfiltered network signaling does cause corresponding radio connection on the mobile device.

22. The method of claim 19, wherein modeling the network signaling further comprises calculating a connection status and a time connected interval based, at least in part, on the one or more calculated CRCS fields.

23. The method of claim 19, wherein modeling the network signaling for the mobile device further comprises calculating signaling efficiency indicating a total number of the radio connections that are saved as a result of the filtering.

24. The method of claim 23, wherein calculating the signaling efficiency further comprises:

accessing a radio log and a traffic activity log associated with the mobile device;

modeling a quantity of virtual radio connections based on the radio log and the traffic activity log,

wherein the virtual radio connections indicate radio connections that would occur but for said filtering;

determining a quantity of actual radio connections based on the radio log,

wherein the total number of the radio connections comprises the difference between the quantity of virtual radio connections and the quantity of actual radio connections.

25. The method of claim 19, wherein modeling the network signaling for the mobile device further comprises calculating a time connected efficiency indicating a total radio connection time saved as a result of the filtering.

26. The method of claim 25, wherein calculating the time connected efficiency further comprises:

accessing a radio log and a traffic activity log associated with the mobile device;

modeling a virtual radio time connected based on the radio log and the traffic activity log,

wherein the virtual radio time connected indicates an amount of time that the mobile device radio would be active but for said filtering;

determining an actual radio time connected based on the radio log,

wherein the actual radio time connected indicates an amount of time that the mobile device radio is active;

wherein the total radio connection time saved comprises the difference between the virtual radio time connected and the actual radio time connected.

27. The method of claim 19, further comprising maintaining the traffic activity log by tracking transactions and measuring the various traffic metrics at the multiple measurement points in the mobile device.

28. The method of claim 19, wherein the one or more CRCS fields are divided into connection flag fields and time connected count fields.

29. The method of claim 19, wherein the one or more CRCS fields are categorized into one or more of the following categories:

actual, simulated, actual simulated, virtual simulated, actual simulated per application, and virtual simulated per application.

30. A mobile device comprising:

a radio;

a processor; and

memory storing instruction, wherein the instructions, when executed by the processor, causes the mobile device to;

access a radio log associated with a mobile device operating in the mobile network, the radio log indicating a state of a mobile device radio;

access a traffic activity log associated with the mobile device, the traffic activity log indicating various traffic metrics measured at multiple measurement points in the mobile device;

calculate one or more CRCS fields based on one or more of the radio log and the traffic activity log; and

model the network signaling for the mobile device based on the one or more CRCS fields.

31. The mobile device of claim 30, wherein the instructions, when executed by the processor, further causes the mobile device to:

determine if transactions initiated by mobile applications executing on the mobile device in the mobile network cause network signaling requiring a corresponding radio connection on the mobile device,

wherein at least a portion of the network signaling caused by the transactions is filtered by a traffic optimization engine,

wherein the filtered network signaling does not cause a corresponding radio connection on the mobile device and the unfiltered network signaling does cause corresponding radio connection on the mobile device.

32. The mobile device of claim 31, further comprising the traffic optimization engine comprising one or more elements of a distributed caching and proxy system.

33. The mobile device of claim 32, wherein the distributed caching and proxy system includes a proxy client and a proxy server, and wherein the filtered radio connections are cached locally by the proxy client.

34. The mobile device of claim 30, wherein the instructions, when executed by the processor, further causes the mobile device to:

track transactions initiated by mobile applications executing on the mobile device in the mobile network;

measure the various traffic metrics at the multiple measurement points in the mobile device; and

maintain the traffic activity log based on the measurements.

35. The mobile device of claim 30, wherein to model the network signaling for the mobile device, the instructions, when executed by the processor, further causes the mobile device to calculate signaling efficiency indicating a total number of the radio connections that are saved as a result of the filtering.

36. The mobile device of claim 30, wherein to calculate the signaling efficiency, the instructions, when executed by the processor, further causes the mobile device to:

access a radio log and a traffic activity log associated with the mobile device;

model a quantity of virtual radio connections based on the radio log and the traffic activity log,

wherein the virtual radio connections indicate radio connections that would occur but for said filtering; and

determine a quantity of actual radio connections based on the radio log,

wherein the total number of the radio connections comprises the difference between the quantity of virtual radio connections and the quantity of actual radio connections.

37. The mobile device of claim 30, wherein to model the network signaling for the mobile device, the instructions, when executed by the processor, further causes the mobile device to calculate a time connected efficiency indicating a total radio connection time saved as a result of the filtering.

38. The mobile device of claim 37, wherein to calculate the time connected efficiency, the instructions, when executed by the processor, further causes the mobile device to:

access a radio log and a traffic activity log associated with the mobile device; and

model a virtual radio time connected based on the radio log and the traffic activity log,

wherein the virtual radio time connected indicates an amount of time that the mobile device radio would be active but for said filtering;

determine an actual radio time connected based on the radio log,

wherein the actual radio time connected indicates an amount of time that the mobile device radio is active;

wherein the total radio connection time saved comprises the difference between the virtual radio time connected and the actual radio time connected.

39. A computer-readable storage medium storing instructions to be implemented by a mobile device having a processor, wherein the instructions, when executed by the processor, causes the mobile device to:

determine if transactions initiated by mobile applications executing on the mobile device in a mobile network cause network signaling requiring a corresponding radio connection,

wherein at least a portion of the network signaling caused by the transactions is filtered by a traffic optimization engine,

wherein the filtered network signaling does not cause a corresponding radio connection; and

modeling the network signaling for the mobile device based, at least in part, on the filtered network signaling.

40. The computer-readable storage medium of claim 39, wherein modeling the network signaling for the mobile device further comprises calculating signaling efficiency indicating a total number of the radio connections that are saved as a result of the filtering.

41. The computer-readable storage medium of claim 39, wherein modeling the network signaling for the mobile device further comprises calculating a time connected efficiency indicating a total radio connection time saved as a result of the filtering.

42. The computer-readable storage medium of claim 39, wherein the instructions, when executed by the processor, further cause the processor to:

access a radio log and a traffic activity log associated with the mobile device,

wherein the radio log indicates a state of a mobile device radio,

wherein the traffic activity log indicates various traffic metrics measured at multiple measurement points in the mobile device; and

maintain the traffic activity log by calculating one or more CRCS fields.

43. The computer-readable storage medium of claim 42, wherein modeling the network signaling is based on the one or more CRCS fields.