This paper focuses on the routing algorithm for the communications between vehicles and places in urban vehicular ad hoc networks. As one of the basic transportation facilities in an urban setting, buses periodically run along their fixed routes and cover many city streets. The trajectory of bus lines can be seen as a submap of a city. Based on the characters of bus networks, we propose a bus-trajectory-based street-centric (BTSC) routing algorithm, which uses buses as the main relay to deliver messages. In BTSC, we build a routing graph based on the trajectories of bus lines by analyzing the probability of bus appearing on every street. We propose two novel concepts, i.e., the probability of street consistency and the probability of path consistency, which are used as metrics to determine routing paths for message delivery. This aims to choose the best path with higher density of busses and lower probability of transmission direction deviating from the routing path. In order to improve the bus forwarding opportunity, we design a bus-based forwarding strategy with ant colony optimization to find a reliable and a steady multihop link between two relay buses in order to decrease the end-to-end delay. The BTSC makes improvements in the selection of routing paths and a strategy of message forwarding. Simulation results show that our proposed routing algorithm has a better performance in terms of the transmission ratio, transmission delay, and adaptability to different networks.

With the development of vehicle networks, the information transmission between vehicles is becoming increasingly important. Many applications, particularly regarding security, are based on communication between vehicles. These applications have strict requirements for factors such as the quality of communication between vehicles and the time delay. Many theoretical communication protocols ignore the presence of buildings or other obstacles that are present during practical use, especially in urban areas. These obstacles can cause a signal to fade or even block direct communication. Many vehicles are often parked at the roadside. Because of their location, these parked vehicles can be used as relays to effectively reduce the shadowing effect caused by obstacles and even solve communication problems. In this paper, we study the problem of parked-vehicle-assistant relay routing communication in vehicle ad hoc networks. We propose an efficient parked vehicle assistant relay routing algorithm that is composed of four parts: a periodic Hello packet exchange mechanism, candidate relay list update, communication link quality evaluation, and candidate relay list selection. Simulation results reveal obvious advantages for indexes such as the quality of communication, success rate, and time delay.

Due to the characteristics of urban vehicular ad hoc networks (VANETs), many difficulties exist when designing routing protocols. In this paper, we focus on designing an efficient routing strategy for vehicle-to-vehicle (V2V) communication in urban VANETs. Because, the characteristics of urban VANET routing performance are affected mainly by intersections, traffic lights, and traffic conditions, we propose an intersection-based distributed routing (IDR) strategy. In view of the fact that traffic lights are used to cause vehicles to stop at intersections, we propose an intersection vehicle fog (IVF) model, in which waiting vehicles dynamically form a collection or fog of vehicles at an intersection. Acting as infrastructure components, the IVFs proactively establish multihop links with adjacent intersections and analyze the traffic conditions on adjacent road segments using fuzzy logic. This approach offloads a large part of the routing work. During routing, the IVFs adjust the routing direction based on the real-time position of the destination, thus avoiding rerouting. Each time an IVF makes a distributed routing decision, the IDR model employs the ant colony optimization (ACO) algorithm to identify an optimal routing path whose connectivity is based on the traffic conditions existing in the multihop links between intersections. Because of the high connectivity of the routing path, the model requires only packet forwarding and not carrying when transmitting along the routing path, which reduces the transmission delay and increases the transmission ratio. The presented mathematical analyses and simulation results demonstrate that our proposed routing strategy is feasible and that it achieves relatively high performance.

Recently, network function virtualization (NFV) has been proposed to solve the dilemma faced by traditional networks and to improve network performance through hardware and software decoupling. The deployment of the service function chain (SFC) is a key technology that affects the performance of virtual network function (VNF). The key issue in the deployment of SFCs is proposing effective algorithms to achieve efficient use of resources. In this paper, we propose a service function chain deployment optimization (SFCDO) algorithm based on a breadth-first search (BFS). The algorithm first uses a BFS based algorithm to find the shortest path between the source node and the destination node. Then, based on the shortest path, the path with the fewest hops is preferentially chosen to implement the SFC deployment. Finally, we compare the performances with the greedy and simulated annealing (G-SA) algorithm. The experiment results show that the proposed algorithm is optimized in terms of end-to-end delay and bandwidth resource consumption. In addition, we also consider the load rate of the nodes to achieve network load balancing.

With the popularization and development of cloud computing, network function virtualization and service function chain (SFC) provisioning have attracted increasing attention from researchers. Excellent and reliable network service is important for network development. Moreover, as the number of network users increases, network service construction costs become very high. Therefore, an efficient algorithm is necessary to provide an SFC with excellent performance and low resource costs. In this paper, we re-examine the problem of optimizing the deployment of an SFC to provide users with excellent and resource-saving network service. We propose a heuristic, closed-loop feedback (CLF) algorithm to find the shortest path to map an SFC. To solve the problem, we introduce and integrate a restricted Boltzmann machine and cross entropy to improve the performance of CLF. Simulation results demonstrate the excellent performance of CLF. The communication delay is reduced by approximately 20%, the accept ratio improves by approximately 15%, and the algorithm running time decreases by approximately 20%. In addition, the resource utilization ratio increases by approximately 15%, and the resource fragmentation ratio decreases by approximately 50%.

Network function virtualization (NFV) in 6G can use standard virtualization techniques to enable network functions via software. Resource scheduling is one of the key research areas of NFV in 6G and is mainly used to deploy service function chains (SFCs) in substrate networks. However, determining how to utilize network resources efficiently has always been a difficult problem in SFC deployment. This article focuses on how to efficiently provision online SFC requests in NFV with 6G. We first establish a mathematical model for the problem of online SFC provisioning. Then, we propose an efficient online service function chain deployment (OSFCD) algorithm that selects the path to deploy that is close to the SFC length. Finally, we compare our proposed algorithm with three other existing algorithms by simulation experiments. The experimental results show that the OSFCD algorithm optimizes multiple performance indicators of online SFC deployment.