# A Terminal-Oriented Distributed Traffic Flow Splitting Strategy for Multi-Service of V2X Networks
## 1 Introduction  
With the rapid development of wireless communication and network technologies, future wireless communication network systems will be heterogeneous networks that include coexistence, fusion, and complementation of multiple networks, such as cellular networks, WLANs (Wireless Local Area Networks), and WPANs (Wireless Personal Area Networks) [1; 2]. In a 5G (5 th-Generation network) vehicle networking scenario, each vehicle is a communication node, and the vehicle network will generate data of different dimensions, different structures, and different properties, which constitute the heterogeneity of the vehicle network [3]. Diversified vehicle networking services and a large number of terminals have put forward high throughput, ultra-low latency, and high stability requirements for the Internet of Vehicles [4; 5]. The 5G communication technology applied in the Internet of Vehicles scenario has prompted vehicle networks to have more flexible architecture and new system elements (5G vehicle OBU (On Board Unit), 5G base stations, 5G mobile terminals, 5G cloud servers, etc.) [6]. In addition to V2X information interactions in the in-vehicle network, the vehicle to vehicle (V2V) network, and the vehicle mobile internet, a 5G vehicle network will also realize the interconnection between the OBU, base station, mobile terminal, and cloud server [7; 8]. In such a hybrid network with multiple types of services, such as network heterogeneity, data heterogeneity, and different QoS (Quality of Service)requirements, determining how to solve the network load, improve the utilization of wireless resources, and improve the quality of the vehicle networking service in the 5G scenario has become an important issue [9]. However, traditional wireless resource management only considers its own network conditions, maximizes the use of network resources, and provides \"best effort\" services, and therefore cannot adapt well to the development of the network. Multi-connection and parallel transmission will break through the limitations on the ability of a single network to provide the stable transmission of services, and give users high-quality transmission services [10; 11]. These problems can be effectively coped with by utilizing traffic flow offloading technology, segmenting traffic flow data streams, and optimizing the communication traffic allocated to each network one by one [12]. Traffic flow diversion is a key part of 5G vehicle networking research. Through proper traffic flow distribution, traffic flow diversion can effectively alleviate the pressure of rapid growth of traffic volume [13]. 5G vehicle networking terminals will carry V2X networking and communication services, as well as vehicle value-added services. Multi-type vehicle services and differentiated traffic service requirements pose a huge challenge to the traditional wireless resource management model. Therefore, in the 5G vehicle network scenario, the coordination of network resources, the optimization of the utilization of wireless resources, and the realization of resource allocation and management of multi-service functionality in a heterogeneous vehicle network is very important. These factors are especially important for the user experience of the vehicle information service. As a multi-attribute decision making approach, the analytical hierarchy process (AHP) efficiently decomposes complex problems into different levels and parts. The parts in the same level are compared and judged. Inspired by AHP, with the priority control based on the queueing theory, the main contributions of this paper are summarized as follows. We also introduce the fundamental ideas of AHP, the priority control, and queueing theory related to our work in Section 2. * We establish the traffic flow splitting model of the multi-service distributed load sharing system to clearly present the 5G V2X communication scenario. * We propose a traffic flow splitting algorithm to improve communication efficiency for 5G V2X communication scenario.