Geo-classification of users from application log data

#Users of applications are spread all over the world. In today's landscape, a user can access an application/service remotely. While user data can be stored over a distributed network to enable remote access, location relating to where the user data is physically stored has become a hot topic. Among other issues, increasing regulation (e.g. international safe harbor privacy principles) will likely result in both users and companies taking a closer look at where data is being stored. As such, examples of the present application are directed to the general technical environment related to geo-classification of users where geo-classification information may be used for data management purposes, among other examples.

#Non-limiting examples of the present disclosure describe evaluation of log data of an application/service for the migration of user data to a data center in a geographic region of a user. Log data for the application/service is evaluated over a given time period on a per user basis. Evaluation of the log data comprises determining, for a user, one or more active days within the given time period. An active day comprises one or more call operations made to the application by the user. A primary geographic region of the user may be determined for the given time period based on analysis of the one or more active days of the log data. One or more data centers may be assigned for storage of user data based on the primary geographic region.

#This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Additional aspects, features, and/or advantages of examples will be set forth in part in the description which follows and, in part, will be apparent from the description, or may be learned by practice of the disclosure.

#Non-limiting and non-exhaustive examples are described with reference to the following figures.

#FIG. 1 is a block diagram illustrating an example of a computing device with which aspects of the present disclosure may be practiced.

#FIGS. 2A and 2B are simplified block diagrams of a mobile computing device with which aspects of the present disclosure may be practiced.

#As more and more users utilize application/services, more data is created. In some examples, data is stored within the United States even when users from other locations (e.g. Europe, Asia, etc.) are accessing such data. Data management may lead to the expansion of data centers in different locations of the world. As new data centers are opened, user data can be migrated closer to where the user is physically located. This improves network performance (e.g. where data being accessed is managed closer to where the user is actually located) by reducing latency when accessing user data, among other examples. Moreover, laws and regulations are constantly evolving where new requirements may be imposed for the management of user data. Migration of user data closer to where a user is located can assist with compliance of laws and regulations for user privacy as well as laws/regulations that will be enforced at a future point in time. Furthermore, migration of user data to data centers where a user may be located can also foster user confidence in an application/service by knowing that user data is stored locally.

#Non-limiting examples of the present disclosure describe evaluation of log data of an application/service for the migration of user data to a data center in a geographic region of a user. Log data for the application/service is evaluated over a given time period on a per user basis. Evaluation of the log data comprises determining, for a user, one or more active days within the given time period. An active day comprises one or more call operations made to the application by the user. In one example, one or more internet protocol (IP) addresses may be identified that are associated with a largest amount of call volume for call operations of a particular active day of user log data. In such an example, a country associated with the one or more IP addresses may be identified, for example, using a mapping that comprises IP address ranges for associated countries. The identified country may be mapped to a particular geographic region. A particular geographic region pertains to a geographic region where the user is located on a particular day (e.g. active day of the given time period). Geographic region data may be aggregated over the given time period, where geographic region data may correspond to a particular geographic region for each of the active days. A primary geographic region of the user may be determined for the user based on analysis of the one or more active days of the log data. A primary geographic region is a location in the world that a user has spent the most time in for the given time period. A primary geographic region may be associated with one or more data centers across the world. In one example, the primary region is determined based on a threshold analysis of the aggregated geographic region data. A data center may be assigned for storage of user data based on the primary geographic region.

#In one particular example, processing operation may be applied that evaluate historical logs for users accessing a storage application/service. IP addresses of log data may be evaluated to first determine the country where a user is located on a particular day. In examples, the country that a user is located in can be mapped to an exemplary particular geographic region. The particular geographic region where the user is located is looked at every day over a given time period (e.g. six-month period) to determine the primary geographic region of the user. Daily location of the user may be analyzed over the given time period rather than the raw call volume over six months in order to prevent a certain day (e.g. uploading a lot of pictures while the user is traveling) to skew the data to a different location.