A microservice recommendation mechanism based on mobile architecture. (15th February 2020)

• Record Type: Journal Article
• Authors: Wang, Ru; Imran, Muhammad; Saleem, Kashif
• Is Part Of: Journal of network and computer applications. Volume 152(2020)
• Publication Date: 2020-02-15
• Subjects: Microservice recommendation mechanism -- GAN -- Trajectory prediction -- Collaborative filtering algorithm; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2019.102510
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: The microservice recommendation mechanism, as a key supporting technology for providing users with intelligent and proactive application services, is one of the important research contents in mobile social networks. In this paper, a recommendation mechanism of mobile social network service based on user trajectory, trust network and collaborative filtering algorithm is proposed. The user trajectory prediction model based on Generative Adversarial Network (GAN) is introduced into the process of service recommendation, and combined with trust degree to constitute the 3D service recommendation model of user-service-trajectory prediction. This method improves the accuracy and reliability of service recommendation and avoids the blindness and randomness of service recommendation. The simulation experiments show that the service recommendation algorithm has higher accuracy than the traditional collaborative filtering algorithm. Highlights: The microservice recommendation mechanism provides users with intelligent and proactive application services. The user trajectory prediction model is based on Generative Adversarial Network (GAN). The trust degree is introduced into the process of service recommendation. The simulation experiments show that the service recommendation algorithm has higher accuracy.