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Method and device for predicting residual online time of peer in peer-to-peer network

  • US 8,280,705 B2
  • Filed: 07/13/2010
  • Issued: 10/02/2012
  • Est. Priority Date: 01/23/2008
  • Status: Active Grant
First Claim
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1. A method for predicting a residual online time of a peer in a peer-to-peer (P2P) network, the method comprising:

  • obtaining, by a peer node in the P2P network, M history life cycle sampling data Si of the peer node, wherein i=1 to M and the history life cycle sampling data comprises a history starting online time point and a history online time of the peer node;

    determining, by the peer node in the P2P network, Gaussian components n in a multidimensional Gaussian Mixture Model to be established, wherein n is a positive integer greater than or equal to 2, and the multidimensional Gaussian Mixture Model denotes a probability distribution of the residual online time of the peer node;

    utilizing, by the peer node in the P2P network, Si and n to establish a multidimensional Gaussian Mixture Model; and

    predicting, by the peer node in the P2P network, the residual online time of the peer node by utilizing the multidimensional Gaussian Mixture Model.

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