Abstract
Social networks are one of the main carriers of information diffusion. Changes in social ties will affect the quality of Device-to-Device (D2D) communications especially the video transmission. For further improving the communication utility of users, it is of great significance to effectively integrate D2D communications and social networks. To this end, this paper utilizes a stochastic approach to modeling and analysis of dynamic social ties in D2D collaborative video transmission. Specifically, a stochastic mathematical model is established and analyzed, in which the combined effect of many factors such as interest, geographical position, career, social class, value system, and interaction is considered. Based on the Brownian motion theory, the strength of social ties among social individuals with time is studied. Next, the reliability function and adaptive parameter estimation are performed. Finally, some examples are conducted to illustrate the main results of this paper, from which one can see that the proposed model has a good predictive ability of the changing trend of social ties.
Highlights
With the development of mobile Internet and wireless communication technology, Device-to-Device (D2D) communications have become one of the key technologies of the future wireless communication and social networks have become one of the main carriers of information diffusion [1].rough D2D communications and social networks, people can communicate with friends and share pictures and videos faster and more conveniently
Since the communication equipment are usually carried by people, the dynamic social environment and a wide range of social applications require D2D communications, especially the D2D collaborative video transmission, to be more selfadapting and to meet more general communication needs
There are users’ mobility and the occurrence of random events in social networks, and changes in users behavior will lead to dynamic interactions between users, which will affect the success rate of users to establish D2D links, thereby affecting the information diffusion [2]. erefore, it is essential to study the D2D collaborative video transmission in conjunction with social networks
Summary
With the development of mobile Internet and wireless communication technology, Device-to-Device (D2D) communications have become one of the key technologies of the future wireless communication and social networks have become one of the main carriers of information diffusion [1]. Xiang et al [11] proposed an unsupervised model, in which the social ties between users were regarded as a latent variable that caused interactive behaviors. Based on this idea, Zhao et al [12] presented a probabilistic generative model, which considers life activities and moving patterns. Inspired by the abovementioned work and based on the fact that the real world is a dynamic environment and it is difficult to gather accurate real-time date to track the changes of social ties, this paper attempts to utilize stochastic processes to study social ties.
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