In the research of heterogeneous wireless network access selection algorithm, the method used for setting network attribute parameter weights is usually simple: using one of the subjective or objective weighting methods: Simple Additive Weighting (SAW), Analytic Hierarchy Process (AHP), Entropy, etc. As a result, the network selection results are incomprehensive. In this paper, we propose a new selection algorithm based on the combination of Intuitionistic Normal Fuzzy Analytic Hierarchy Process (INFAHP) and Improved Grey Relation Analysis (IGRA), which has been proved to be a new Multiple Attribute Decision Making (MADM) method based on the combination of subjective and objective weights. This algorithm expresses the semantic importance of the intuitionistic normal fuzzy number and calculates the subjective weight of network attributes using INFAHP while obtaining the objective weight using Coefficient of Variation (CV) at the same time. The final weights are integrated by subjective and objective weights. After that, the candidate networks can be sorted using IGRA. The proposed algorithm can get the more comprehensive weights of the network attributes by integrating the subjective and objective weights. Simulation results show that our algorithm can reduce the ratio of network handovers by 25% in average in the four traffic classes and improve the ping-pong effect effectively, so as to better meet users’ demands for QoS.
A heterogenous network selection algorithm for internet of vehicles based on comprehensive weight