Fuzzy multi-attribute utility based network selection approach for high-speed railway scenario

Due to the complexity and fluctuation of the wireless network state in high-speed mobility scenarios, the existing works related to network selection face a great challenge for selecting the accurate network in terms of the imprecise information and mobility. Therefore, we design a novel dynamic imprecise-aware network selection approach, named FSNS by taking advantage of fuzzy logic and utility function of multiple attributes. Our proposed approach not only copes with imprecise network information but also dynamically adapts to the high-speed mobility scenarios, which are not presented for the existing proposals. In this paper, we compare FSNS approach with an enhanced TOPSIS method through simulation experiments of two types of services. The results demonstrate that FSNS outperforms TOPSIS for a preferable decision to keep relatively stable and reduce abnormal selection. The conclusions of experimental results have some extent pragmatic value because the simulation imitates network state in the high-speed mobile environment by real world data from high-speed railways.