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The prevalence of mobile devices has spurred human mobility to be applied in mobile networking and communications by using network science, in which the temporal evolution of a network topology is of great importance for protocol design and performance analysis. This paper focuses on link generation in a temporal evolution network. Based on observations revealing the strong correlation between the connection patterns of different time periods, a link generation potential based on historical connections is proposed in this paper, aiming to provide a method for making topological predictions with less randomness. Using MIT Reality dataset, an evaluation of the accuracy of the proposed method was conducted. The experimental results demonstrate the proposal’s adequacy in terms of its accuracy.
The prevalence of mobile devices has spurred human mobility to be applied in mobile networking and communications by using network science, in which the temporal evolution of a network topology is of great importance for protocol design and performance analysis. This paper focuses on link generation in a Based on observations revealing the strong correlation between the connection patterns of different time periods, a link generation potential based on historical connections is proposed in this paper, aiming to provide a method for making topological predictions with less randomness. Using MIT Reality dataset, an evaluation of the accuracy of the proposed method was conducted. The experimental results demonstrate the proposal’s adequacy in terms of its accuracy.