Optimizing keepalive and other background traffic in a wireless network

• US 9,820,330 B2
• Filed: 08/12/2016
• Issued: 11/14/2017
• Est. Priority Date: 06/11/2013
• Status: Expired due to Fees

• Current Assignee: Seven Networks LLC (FIG LLC (d/b/a Fortress Investment Group LLC))
• Original Assignee: Seven Networks LLC (FIG LLC (d/b/a Fortress Investment Group LLC))
• Inventors: Nirantar, Abhay, Kokhanovskyi, Andrii, Batlivala, Nariman D., Al-Isawi, Rami, Yoon, Sungwook, Fleming, Michael, Backholm, Ari
• Primary Examiner(s): Scheibel, Robert C
• Application Number:
  US15/235,241
• Publication Number:
  US 20170094710A1
• Time in Patent Office: 459 Days
• Field of Search: None
• CPC Class Codes: H04L 5/0053 Allocation of signaling, i.e. of overhead other than pilot signals
• CPC Class Codes: H04L 67/5682 Policies or rules for updating, deleting or replacing the stored data
• CPC Class Codes: H04L 69/16 Implementation or adaptation of Internet protocol [IP], of transmission control protocol [TCP] or of user datagram protocol [UDP]
• CPC Class Codes: H04W 12/00 Security arrangements; Authentication; Protecting privacy or anonymity
• CPC Class Codes: H04W 24/02 Arrangements for optimising operational condition
• CPC Class Codes: H04W 28/0231 based on communication conditions dynamic wireless traffic scheduling definition based on channel quality criteria H04W72/54
• CPC Class Codes: H04W 52/0251 using monitoring of local events, e.g. events related to user activity
• CPC Class Codes: H04W 52/0258 controlling an operation mode according to history or models of usage information, e.g. activity schedule or time of day
• CPC Class Codes: H04W 72/51 based on terminal or device properties
• CPC Class Codes: H04W 76/20 Manipulation of established connections
• CPC Class Codes: H04W 76/25 Maintenance of established connections
• CPC Class Codes: H04W 88/02 Terminal devices
• CPC Class Codes: Y02D 30/70 in wireless communication networks

Abstract

Systems and methods for optimizing keepalives or other non-interactive or background traffic from applications on a mobile device are disclosed. A keepalive optimizer can detect keepalive and other background traffic and optimize such traffic by blocking keepalives, advancing or delaying execution of keepalives, delaying repeatable background requests based on radio state, device state or characteristics, policy, transaction characteristics, application characteristics, and/or the like. The disclosed keepalive optimization methods facilitate management of traffic and/or conservation of resources on the mobile device and the network. The keepalive optimization can be performed by an application sending the keepalives or by a local proxy on the mobile device.

Claims

1. A method comprising:

gathering keepalive messages between a mobile device and a remote entity for a training period, wherein the keepalive messages are defined by at least one of a plurality of keepalive predictor data;

storing the keepalive messages in a local database storage;

applying a predetermined first set of rules to separate the keepalive messages into a group of safe keepalive messages and a group of unsafe keepalive messages;

creating a second set of rules for identifying safe keepalive messages by;

creating subrules based on each of the plurality of keepalive predictor data;

applying each of the subrules to the keepalive messages to identify and remove safe keepalive messages from the keepalive messages until no more safe keepalive messages can be identified;

creating a list of the subrules that were applied;

intercepting a current keepalive message between a mobile device and a remote entity;

determining whether the current keepalive message is a safe keepalive message by applying the second set of rules to the current keepalive message; and

in response to a determination that the current keepalive message is a safe keepalive message, blocking the current keepalive message from reaching the remote entity.

2. The method of claim 1, wherein the predetermined first set of rules are based on a first keepalive predictor data.

3. The method of claim 1, wherein creating a second set of rules for identifying safe keepalive messages further comprises:

applying a third set of rules to each of the subrules in the list to determine the subrules'"'"' probabilities of successfully identifying safe keepalive messages; and

rearranging the list of subrules from highest to lowest probability of successfully identifying safe keepalive messages.

4. The method of claim 1, wherein the keepalive predictor data is one of user, application, time-of-day, day-of-week, screen state pattern, screen use pattern, number of safe keepalive messages in the immediate past, unnecessary chain length, size of the keepalive message, and TCP session order.

5. The method of claim 2, wherein the first keepalive predictor data is unnecessary chain length.

6. A mobile device comprising:

a processor;

a memory;

a communications interface;

the processor being configured to;

gather keepalive messages between the mobile device and a remote entity for a training period, wherein the keepalive messages are defined by at least one of a plurality of keepalive predictor data;

store the keepalive messages in a memory;

apply a predetermined first set of rules to separate the keepalive messages into a group of safe keepalive messages and a group of unsafe keepalive messages;

create a second set of rules for identifying safe keepalive messages by;

creating subrules based on each of the plurality of keepalive predictor data, wherein the subrules identify safe keepalive messages;

applying each of the subrules one at a time to the keepalive messages to identify and remove safe keepalive messages from the keepalive messages until no more safe keepalive messages can be identified;

creating a list of the subrules that were applied;

intercept a current keepalive message between a mobile device and a remote entity;

determine whether the current keepalive message is a safe keepalive message by applying the second set of rules to the current keepalive message; and

in response to a determination that the current keepalive message is a safe keepalive message, block the current keepalive message from reaching the remote entity.

7. The mobile device of claim 6, wherein the predetermined first set of rules are based on a first keepalive predictor data.

8. The mobile device of claim 6, wherein the processor is further configured to:

apply a third set of rules to each of the subrules in the list to determine the subrules'"'"' probabilities of successfully identifying safe keepalive messages; and

rearrange the list of subrules from highest to lowest probability of successfully identifying safe keep alive messages.

9. The mobile device of claim 6, wherein the keepalive predictor data is one of user, application, time-of-day, day-of-week, screen state pattern, screen use pattern, number of safe keepalive messages in the immediate past, unnecessary chain length, size of the keepalive message, and TCP session order.

10. The mobile device of claim 7, wherein the first keepalive predictor data is unnecessary chain length.

11. A computer program product comprising:

a computer readable storage medium containing a computer readable program code configured to;

gather keepalive messages between a mobile device and a remote entity for a training period, wherein the keepalive messages are defined by at least one of a plurality of keepalive predictor data;

store the keepalive messages in a memory;

apply a predetermined first set of rules to separate the keepalive messages into a group of safe keepalive messages and a group of unsafe keepalive messages;

create a second set of rules for identifying safe keepalive messages by;

creating subrules based on each of the plurality of keepalive predictor data, wherein the subrules identify safe keepalive messages;

applying each of the subrules one at a time to the keepalive messages to identify and remove safe keepalive messages from the keepalive messages until no more safe keepalive messages can be identified;

creating a list of the subrules that were applied;

intercept a current keepalive message between a mobile device and a remote entity;

determine whether the current keepalive message is a safe keepalive message by applying the second set of rules to the current keepalive message; and

in response to a determination that the current keepalive message is a safe keepalive message, block the current keepalive message from reaching the remote entity.

12. The computer program product of claim 11, wherein the predetermined first set of rules are based on a first keepalive predictor data.

13. The computer program product of claim 11, wherein the computer readable program code is further configured to:

apply a third set of rules to each of the subrules in the list to determine the subrules'"'"' probabilities of successfully identifying safe keepalive messages; and

rearrange the list of subrules from highest to lowest probability of successfully identifying safe keepalive messages.

14. The computer program product of claim 11, wherein the keepalive predictor data is one of user, application, time-of-day, day-of-week, screen state pattern, screen use pattern, number of safe keepalive messages in the immediate past, unnecessary chain length, size of the keepalive message, and TCP session order.

15. A system comprising:

a network;

a host server comprising;

a server cache;

a proxy server configured to;

receive requests from a mobile device over the network;

return content and data to the mobile device in response to the requests over the network;

the mobile device further comprising;

a local data cache;

a local proxy server configured to;

gather keepalive messages between the mobile device and the host server for a training period, wherein the keepalive messages are defined by at least one of a plurality of keepalive predictor data;

store the keepalive messages in a local data cache;

apply a predetermined first set of rules to separate the keepalive messages into a group of safe keepalive messages and a group of unsafe keepalive messages, wherein the predetermined first set of rules are based on a first keepalive predictor data;

create a second set of rules for identifying safe keepalives by;

creating subrules based on each of the plurality of keepalive predictor data, wherein the subrules identify safe keepalive messages;

applying each of the subrules one at a time to the keepalive messages to identify and remove safe keepalive messages from the keepalive messages until no more safe keepalive messages can be identified;

creating a list of the subrules that were applied;

applying a third set of rules to each of the subrules m the list to determine the subrules'"'"' probabilities of successfully identifying safe keepalive messages;

rearranging the list of subrules from highest to lowest probability of successfully identifying safe keepalive messages;

intercept a current keepalive message between a mobile device and the host server;

determine whether the current keepalive message is a safe keepalive message by applying the second set of rules to the current keepalive message;

in response to a determination that the current keepalive message is a safe keepalive message, block the current keepalive message from being sent to the host server; and

a network communications interface for sending requests and keepalive messages to the host server.