Open AccessModel of Data Collection Control in the Internet of Things on the Basis of Social Network Technologies
Author(s) -
Nataly Zhukova,
Aung Myo Thaw,
Elena Evnevich
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1864/1/012093
Subject(s) - friendship , computer science , data collection , the internet , node (physics) , social network (sociolinguistics) , cluster analysis , relation (database) , data mining , control (management) , basis (linear algebra) , computer network , data science , world wide web , artificial intelligence , engineering , mathematics , social media , sociology , social science , statistics , geometry , structural engineering
The paper deals with the issues of data collection in the dynamic Internet of Things network. An approach proposed is based on the models and methods of social networks analysis along with clustering methods commonly used in this case. The developed hybrid model tracks contacts between nodes of the network thus creating “social relationships” for each node and estimates the number and the frequency of “social contacts” characterizing the degree of “friendships”. After fixing the contacts between nodes the model takes into consideration only the nodes connected by “friendship” relation. Data collection based on “social structure” provides higher security level and shows the enhancement as regards energy saving and delays of data transfer.