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Retracted: Artificial intelligence point‐to‐point signal communication network optimization based on ubiquitous clouds
Author(s) -
Hong Lin,
Deng Lianbing,
Li Daming,
Wang Harry Haoxiang
Publication year - 2021
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.4507
Subject(s) - computer science , scheme (mathematics) , artificial intelligence , point (geometry) , optimization problem , cloud computing , distributed computing , signal (programming language) , algorithm , mathematical analysis , geometry , mathematics , operating system , programming language
Summary At present, the application of communication network has spread to every area of social life. The progress of network technology has driven the development of information technology industry and the advancement of cloud computing. With the application of artificial intelligence and deep learning technology, the network becomes more and more intelligent, so the application of artificial intelligence theory in communication network optimization modeling is more extensive. In this paper, we propose the ubiquitous clouds framework and apply the artificial intelligence optimization scheme to the point‐to‐point (P2P) signal transmission network optimization scheme. For different application scenarios, this paper analyzes and experiments the proposed method. The experimental results show that the proposed method makes full use of the advantages of communication network resources which improves the efficiency of communication network optimization and also reduces the optimization cost to a certain extent compared with the state‐of‐the‐art approaches.