Log information network structuring method and log information network structuring system based on P2P program requesting system
A network structure and on-demand system technology, applied in the field of P2P network and community detection algorithm, can solve the problems of community structure rationality, effectiveness and stability to be improved
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Embodiment 1
[0054] like figure 1 and 2 Shown, a kind of log information network structure method based on P2P on-demand system, comprises the following steps:
[0055] Step 1: Collect user log information;
[0056] Step 2: According to the log information of the nodes, construct a community network structure with users as nodes, relationships between users as edges, and weights expressed by node bandwidth;
[0057] The connection relationship between nodes is calculated by the following algorithm flow:
[0058] 1) The user ID is used as an identifier, and the number of Peers playing the same video URL and the ID of the Peer can be counted at a certain moment, so that a network structure relationship without weight can be formed between nodes.
[0059] 2) Set the weight coefficient according to the bandwidth relationship of the user, so as to form a network structure with weight.
[0060] The above is a coarse-grained calculation process. On the basis of the above calculation process, ...
Embodiment 2
[0105] This embodiment provides a system for implementing the log information network structuring method based on the P2P on-demand system described in Embodiment 1, including the following structure:
[0106] Log collection module 1, used to collect log information of users;
[0107] The community network structure construction module 2 is used to construct a community network structure with users as nodes, relationships between users as edges, and weights represented by node bandwidth according to the user's log information;
[0108] The community structure division module 3 is used to divide the community network structure according to the LabelRank algorithm to obtain multiple communities;
[0109] The LabelRank algorithm relies on 4 operators:
[0110] 1. Transfer operation
[0111] The transfer operation is specifically: define a 1×n vector P at each node to store label distribution, n is the number of nodes; define an adjacency matrix A to store the network structure,...
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