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Marginal hierarchical social relation perception method

A social relationship and edge technology, applied in the field of edge layered social relationship perception, which can solve the problems of heavy computing burden on centralized servers and transmission link burden.

Active Publication Date: 2018-05-08
BEIJING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

[0006] However, when the above algorithm is applied to the actual network, the centralized social relationship perception has the following problems: the centralized server has a heavy computational burden, and a large amount of raw data collected from the edge of the network needs to be uploaded to the centralized server, which will give the corresponding transmission link Bring a greater burden

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Embodiment Construction

[0032] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0033] In describing the present invention, it should be understood that the terms "center", "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", " The orientations or positional relationships indicated by "vertical", "horizontal", "top", "bottom", "inner" and "outer" are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and Simplified descriptions, rather than indicating or implying that the device or element refe...

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Abstract

The invention provides a marginal hierarchical social relation perception method. A semi-supervised algorithm is decomposed into N+1 parallel subtasks to be allocated to the centralized server and theN F-APs for training and prediction for the centralized server and N fog computing access points (F-AP) of a fog wireless access network based on the integrated semi-supervised algorithm by using multiple classification and regression tree (CART) models for parallel training and prediction so as to reduce the computing burden of the centralized server. The position information required for socialrelation perception is acquired from the F-APs and the conversation record information is acquired from the centralized server. The centralized server and the N F-APs perform parallel computing so that the time overhead can be reduced; and the centralized server and the N F-APs only require to perform information interaction of small data volume with no requirement for uploading all the originaldata to the centralized server so that the burden of the pre-transmission link can be reduced.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a method for sensing edge-layered social relations. Background technique [0002] With the increase in the penetration rate of smart terminals and the explosive growth of the usage of data services and multimedia services, wireless networks are facing the problem of capacity shortage. Device-to-Device Direct (D2D) communication is recognized as a promising technology, which allows two devices with close physical distance to communicate directly, which can improve spectrum efficiency and increase system capacity. However, D2D communication faces some unresolved problems. For security considerations and users’ selfishness, users will not conduct D2D communication with strangers. If users cannot judge whether the object requesting D2D is recognized, they may reject D2D. Communication requests, thus limiting the application of D2D in actual networks. [0003] At pres...

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Application Information

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IPC IPC(8): H04L12/24H04L29/08H04W4/02H04W4/24G06N3/00
CPCG06N3/006H04L41/145H04L41/147H04L67/10H04W4/02H04W4/24
Inventor 彭木根张朝亮孙耀华
Owner BEIJING UNIV OF POSTS & TELECOMM
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