Artificial intelligence point‐to‐point signal communication network optimization based on ubiquitous clouds. (2nd July 2020)

• Record Type: Journal Article
• Authors: Hong, Lin; Deng, Lianbing; Li, Daming; Wang, Harry Haoxiang
• Other Names: Suma V. guestEditor.; Fernando Xavier guestEditor.; Palanisamy Ram guestEditor.; Bestak Robert guestEditor.
• Is Part Of: International journal of communication systems. Volume 34:Number 6(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-07-02
• Subjects: artificial intelligence -- communication network -- neural network optimization -- particle swarm optimization (PSO) -- point‐to‐point transmission -- ubiquitous clouds; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.4507
• Languages: English
• ISSNs: 1074-5351

Abstract

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.