Behavior prediction based on interest characteristic and user communication in opportunistic social networks

Abstract

With the rapid popularization of mobile smart devices in 5G communication, social networks become important message dissemination platforms. Information could be delivered through users formed by moving nodes in social network. However, a great number of data are transmitted and then they have brought greater load to the entire network. How to improve this transmission environment has become an issue. This work proposes a method that could select cooperative users based on interest and behavior. Data communication in opportunistic social network, the degree of node preferences is calculated, and highly matched nodes are selected for priority transmission. This method reduces the occupation of cache resources by redundant information in the network by filtering the message transmission mode of the cooperative nodes, and improves the space utilization of the message cache. Experimental results show that the method is superior to other algorithms in the experiment in terms of data delivery rate, average delay, and routing overhead.

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Funding

this work was supported in The National Natural Science Foundation of China(61672540); Hunan Provincial Natural Science Foundation of China (2018JJ3299, 2018JJ3682).

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Correspondence to Jia Wu.

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Wu, J., Qu, J. & Yu, G. Behavior prediction based on interest characteristic and user communication in opportunistic social networks. Peer-to-Peer Netw. Appl. 14, 1006–1018 (2021). https://doi.org/10.1007/s12083-020-01060-8

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Keywords

  • Opportunistic social networks
  • Behavior prediction
  • User
  • Delivery rate
  • Average delay