Social relation predictive model of mobile nodes in internet of things

With the development of Internet of Things, humans with smart multimedia devices are a new trend of mobile-aware service. This new mode of awareness will inevitable brings some challenges. Among them, the quantification of social relations is the basis of mobile-aware service, and it is an abstract psychological cognitive process, involving space, time and behaviour. Therefore, using social network theory, a novel quantization and predication model with multiple decision factors is proposed, in which multiple decision factors including location, call records, service and feedback factors. These factors are incorporated to reflect the complexity and uncertainty of social relations. Also, the weight distribution is set up by information entropy, and support vector machines optimized based genetic algorithm is used to predict the social relations of mobile nodes, which overcomes the shortage of traditional method, in which the weight is set up by subjective manners and has poor dynamic adaptability. Simulation results show that, cognitive model has better predictive accuracy and dynamic adaptability.