Socially-aware mobile networks have become ubiquitous in our daily life, which create the phenomenon of the socially aware mobile big data. Due to the movement of mobile entities, traditional transmission mechanisms are not conducive to the spreading of information. Thus, how to improve the information diffusion performances in socially aware mobile networks has become a hot research topic. However, most of the existing works focus their attention on the information-spreading dynamics rather than on the network structure and nodes' social attributes. In this paper, we proposed the concept of the value strength, social strength as well as a time-varying graph (TVG)-based mobility model from the perspective of the network science, based on which a forwarding nodes' selection scheme was presented. It is beneficial in terms of improving the propagation efficiency and information coverage ratio of mobile networks. Furthermore, sufficient experiments were conducted to verify the diffusion performances both over a range of complex network topologies, such as the Watts-Strogatz small-world network, the Barabási-Albert scale-free network, the real-world Flickr network, and over a TVG-based mobile network. Indeed, the definition of the value/social strength plays a critical role in selecting forwarding links and nodes both for static-topology networks as well as for socially aware mobile networks.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Materials Science(all)