Artificial intelligence point‐to‐point signal communication network optimization based on ubiquitous clouds. (2nd July 2020) - Hong, Lin; Deng, Lianbing; Li, Daming; Wang, Harry Haoxiang
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. Abstract : This paper presents the ubiquitous clouds framework and applies the artificial intelligence optimization scheme to the point‐to‐point (P2P) signal transmission network optimization scheme. 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; proposed method can handle the signal transmission complexity.