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System and method for mobile platform virtualization

  • US 9,063,770 B2
  • Filed: 12/11/2012
  • Issued: 06/23/2015
  • Est. Priority Date: 12/11/2012
  • Status: Active Grant
First Claim
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1. A method for a mobile platform containing a mobile terminal having an operating system, comprising:

  • virtualizing hardware components of the mobile terminal by a virtualization layer in the operating system;

    initializing a plurality of user environments (UEs) on the mobile terminal through the virtualization layer over the operating system, including a first current UE and a second current UE running independently in parallel on the mobile terminal, wherein the plurality of UEs share the same hardware components and are switched among one another based on one or more predetermined conditions without changing the operating system;

    collecting sensing data on certain parameters associated with operation of the mobile terminal;

    processing the sensing data to indicate at least one of the one or more predetermined conditions of the mobile terminal;

    determining whether the first current UE suits the at least one of the one or more predetermined conditions of the mobile terminal indicated by processing the sensing data; and

    when the first current UE does not suit the one or more predetermined conditions of the mobile terminal, switching the first current UE to a desired UE from the plurality of UEs;

    wherein processing the sensing data includes;

    forwarding the sensing data to a server in a cloud;

    providing a user behavior database in the server, including a learned database to match the sensing data;

    receiving an input of a user, including a label of an event created by the user, to facilitate a user behavior analysis, wherein the input is not user-specific and personal information of the user and private information of the user are not stored;

    performing the user behavior analysis based on the sensing data on the server;

    learning user behavior according to the user behavior analysis and the learned database; and

    updating the user behavior database in an adaptive mode during run-time.

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