Mathematical model of multi-criteria balancing of V2X-system parameters

The development of intelligent transportation systems and the introduction of V2X (Vehicle-to-Everything) architecture place high demands on the characteristics of network communication, such as minimum latency, high reliability, and energy efficiency. At the same time, a decrease in one of the parameters entails an increase in another, which makes the task of their balanced tuning relevant and practically significant. It is especially important to consider not only the total delay (communication network delay and computational delay) and energy consumption, but also the expected arrival time of a mobile computing node based on a vehicle, which is an integral indicator of service quality in a dynamically changing environment. In this paper, we propose a mathematical model for multi-parameter optimization of V2X-system operation parameters that takes into account three interrelated indicators: total delay, energy consumption, and expected arrival time. The model formalizes the structure of the transport system as a directed graph with specified traffic routes, the location of stationary and mobile computing nodes of the transport infrastructure, and the parameters of video data exchange between them and terminal devices. The model is presented as an optimization problem and allows tuning the system according to external conditions and application goals. Simulation modeling methods with realistic vehicle traffic scenarios and variable network load are used as a research tool. The results of numerical experiments demonstrate that the use of the proposed model will allow achieving more balanced modes of system operation, reducing the total delays and energy consumption without deterioration of the arrival time parameters. Compared to traditional approaches based on single- or two-criteria optimization, the proposed method provides greater adaptability and stability of V2X systems to changing operating conditions. The findings can be useful for researchers in designing and implementing energy-efficient and reliable distributed architectures in modern transportation networks.