Social graph based co-location of network users

• US 10,223,397 B1
• Filed: 03/13/2015
• Issued: 03/05/2019
• Est. Priority Date: 03/13/2015
• Status: Active Grant

• Current Assignee: Snap, Inc.
• Original Assignee: Snap, Inc.
• Inventors: Sehn, Timothy Michael, Son, Aaron
• Primary Examiner(s): Obisesan, Augustine K.
• Application Number:
  US14/658,115
• Time in Patent Office: 1,453 Days
• CPC Class Codes: G06F 16/2291 User-Defined Types; Storage management thereof
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 43/0811 by checking connectivity
• CPC Class Codes: H04L 43/0882 Utilisation of link capacity
• CPC Class Codes: H04L 67/1008 based on parameters of servers, e.g. available memory or workload monitoring of computer activity G06F11/30
• CPC Class Codes: H04L 67/1021 based on client or server locations
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

User activity in a communication network is monitored to obtain social graph data for each user. This social graph data is used to cluster the users into groups of users that interact with each other regularly. The groups are analyzed to generate a profile for each group with respect to a set of relevant data points. The profiles can be based on identifying group social graph data that is related to a data point (e.g., user activity level) that is being used to provision network server resources. The profile for each group is then compared to corresponding data associated with a plurality of servers providing network services to the users. Each group is then assigned to one or more of the servers that best matches the profile of the group. Servers may be added to the network by comparing data regarding a proposed new server to existing group profiles.

Claims

1. A method comprising:

monitoring, using one or more processors, network activity of a plurality of users of a communication network;

generating social graph data for each user in the plurality of users based on the monitored network activity;

calculating a connectivity measure between each pair of users in the plurality of users based on the social graph data, the connectivity measure comprising a level of communication between users in each pair of users, wherein the level of communication includes a frequency of communication between the users in each pair of users;

identifying a geographic area associated with each of the plurality of users;

clustering the plurality of users into a plurality of groups based on the connectivity measures between each pair of users and based on the geographic area associated with each of the plurality of users; and

selecting a plurality of servers to be assigned to the plurality of groups, respectively,

wherein selecting a first server included in the plurality of servers to be associated to a first group included in the plurality of groups includes;

selecting the first server that is at least one of;

within the geographic area associated with the first group, having a capacity to support an activity level associated with the users in the first group, or having assets available that are utilized by the users in the first group, and

causing mobile devices associated with the users in the first group to access network resources from the first server.

2. The method of claim 1, wherein the connectivity measure comprises one or more of:

a level of similarity of navigation patterns between each pair of users, a level of similarity of user profiles between each pair of users, and a level of similarity of user contacts between each pair of users.

3. The method of claim 1, further comprising:

comparing one or more of activity level data and asset utilization data for each of the plurality of groups to corresponding one or more of activity level and asset utilization data associated with each of the plurality of servers.

4. The method of claim 3, wherein the one or more of the activity level data and asset utilization data for each of the plurality of groups is an average of the one or more of the activity level data and asset utilization data for users included in each of the plurality of groups.

5. A system comprising:

a processor; and

memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to;

monitor network activity of a plurality of users of a communication network;

generate social graph data for each of the users based on the monitored activity;

calculate a connectivity measure between each pair of users in the plurality of users based on the social graph data, the connectivity measure comprising a level of communication between users in each pair of users, wherein the level of communication includes a frequency of communication between the users in each pair of users;

identify a geographic area associated with each of the plurality of users;

cluster the plurality of users into a plurality of groups based on the connectivity measures between each pair of users and based on the geographic area associated with each of the plurality of users; and

select a plurality of servers to be assigned to the plurality of groups, respectively,

wherein to select a first server included in the plurality of servers to be associated to a first group included in the plurality of groups includes to;

select the first server that is at least one of;

within the geographic area associated with the first group, having a capacity to support an activity level associated with the users in the first group, or having assets available that are utilized by the users in the first group, and

to cause mobile devices associated with the users in the first group to access network resources from the first server.

6. The system of claim 5, wherein the connectivity measure comprises one or more of:

a level of similarity of navigation patterns between each pair of users, a level of similarity of user profiles between each pair of users, and a level of similarity of user contacts between each pair of users.

7. The system of claim 5, wherein the memory further stores instructions for causing the system to:

compare one or more of activity level data and asset utilization data for each of the plurality of groups to corresponding activity level and asset utilization data associated with each of the plurality of servers.

8. The system of claim 7, wherein the one or more of the activity level data and asset utilization data for each of the plurality of groups is an average of the one or more of the activity level data and asset utilization data for users included in each of the plurality of groups.

9. A non-transitory computer-readable medium storing instructions that, when executed by a computer system, cause the computer system to perform operations comprising:

monitoring network activity of a plurality of users of a communication network;

generating social graph data for each user in the plurality of users based on the monitored activity;

calculating a connectivity measure between each pair of users in the plurality of users based on the social graph data, the connectivity measure comprising a level of communication between users in each pair of users, wherein the level of communication includes a frequency of communication between the users in each pair of users;

clustering the plurality of users into a plurality of groups based on the connectivity measures between each pair of users and based on a geographic area associated with each of the plurality of users; and

selecting a plurality of servers to be assigned to the plurality of groups, respectively,

wherein selecting a first server included in the plurality of servers to be associated to a first group included in the plurality of groups includes;

selecting the first server that is at least one of;

within the geographic area associated with the first group, having a capacity to support an activity level associated with the users in the first group, or having assets available that are utilized by the users in the first group, and

causing mobile devices associated with the users in the first group to access network resources from the first server.

10. The computer-readable medium of claim 9, wherein the connectivity measure comprises one or more of:

a level of similarity of navigation patterns between each pair of users, a level of similarity of user profiles between each pair of users, and a level of similarity of user contacts between each pair of users.

11. The computer-readable medium of claim 10, the operations further comprising:

comparing one or more of activity level data and asset utilization data for each of the plurality of groups to corresponding one or more of activity level and asset utilization data associated with each of the plurality of servers.

12. The computer-readable medium of claim 11, wherein the one or more of the activity level data and asset utilization data for each of the plurality of groups is an average of the one or more of the activity level data and asset utilization data for users included in each of the plurality of groups.