A Network Selection Strategy Based on Joint Optimization of User Satisfaction and Transmission Efficiency in Internet of Vehicle

Abstract

Network selection in the Internet of Vehicles has become a popular topic of research. Unlike existing algorithms for heterogeneous network environments that rarely consider user satisfaction, in this paper, we propose a network selection strategy that takes into account both user satisfaction and transmission efficiency. We employ the effective capacity concept, which describes the maximum throughput a system can achieve under a specific statistical Quality-of-Service (QoS) delay violation probability constraint. This strategy first analyzes the influence of different utility function weight coefficients, transmission power, and time delay on each network utility satisfaction function. It is evident that the weight coefficient is proportional to the value of the utility function. Within a constrained transmission power range, the rate of increase of the function gradually slows down until it approaches a fixed value. When the delay factor value is larger, the function value is smaller, which indicates that the pursuit of lower delay will sacrifice other network performance aspects. In order to determine the maximum value of each network utility satisfaction function, a convex optimization theory is introduced for the joint optimization of user satisfaction and transmission efficiency. Finally, simulation experiments carried out under three representative network environments show that the proposed strategy is efficient and reliable.