Abstract
In recent years, the application of intelligent transportation systems has gradually made the transportation industry safe, efficient, and environmentally friendly and has led to a broader research prospect of vehicle wireless communication technology. Distributed vehicular self‐organizing networks are mobile self‐organizing networks in realistic traffic situations. Data interaction and transmission between nodes are achieved through the establishment of a vehicular self‐organizing network. In this paper, a multipath routing protocol considering path stability and load balancing is proposed to address the shortcomings of existing distributed vehicular wireless self‐organizing routing protocols. This protocol establishes three loop‐free paths in the route discovery phase and uses the path stability parameter and load level parameter together to measure the total transmission cost. The one with the lowest total transmission cost is selected as the highest priority path for data transmission in the route selection phase, and the other two are used as alternate paths, and when the primary path breaks, the higher priority of the remaining path will continue to transmit data as the primary route. In this paper, to improve the content distribution performance of target vehicles in scenarios where communication blind zones exist between adjacent roadside units, an assisted download distribution mechanism for video‐like large file content is designed in the V2V and V2I cooperative communication regime. That is, considering a two‐way lane scenario, we use the same direction driving vehicles to build clusters, reverse driving vehicles to carry prefetched data, and build clusters to forward prefetched data to improve the data download volume of target vehicles in nonhot scenarios such as highways with the sparse deployment of roadside units, to meet the data volume download demand of in‐vehicle users for large files and give guidance for efficient distribution of large file content in highway scenarios.
Highlights
In recent years, with the rapid development of wireless communication technology, the Internet of Vehicles (IoV), as an important branch of the Internet of Things (IoT), has received more and more attention from governments, research institutions, and enterprise manufacturers
Incorporating sensor, image processing, vehicle positioning, and other sensing technologies, wireless communication, heterogeneous network fusion, and other network technologies, as well as cloud computing, mobile edge computing, big data, and other application technologies, IoV can realize the network communication between each module inside the vehicle [1], vehicle and vehicle occupants, vehicle and vehicle, vehicle and pedestrian, and vehicle and roadside facilities, which can be used for urban network interconnection, intelligent traffic management, intelligent city construction, vehicle autonomous driving, and other industry fields to provide active assistance and effective support and provide a variety of technical solutions to the abovementioned urban traffic management problems [2]
When M < 50, the video requesting vehicle enters the communication range of the roadside unit and starts downloading video streams, and when driving away from the communication range, the video requesting vehicle will rely on the relay node to continue establishing communication links with the roadside unit, so the QDAVS mechanism and our proposed mechanism obtain significantly better data volume than the TAVS mechanism; in addition, we use the TOPSIS-based; we use the TOPSIS-based multicriteria decision method to select the optimal relay node to establish a communication link with higher download and transmission rates and
Summary
With the rapid development of wireless communication technology, the Internet of Vehicles (IoV), as an important branch of the Internet of Things (IoT), has received more and more attention from governments, research institutions, and enterprise manufacturers. The application is mostly broadcastbased, to ensure the dissemination coverage of safety information, so the design and development need to consider solving the broadcast storms and other collateral problems; propagation distance, because it is mainly communication between adjacent vehicles, the number of forwarding hops is small, and most of them are single-hop, that is, direct communication is the main (2) Traffic Management Category This class of applications is mainly aimed at solving road traffic management-related problems; on the one hand, with the vehicle self-organizing network and roadside units to collect real-time information on vehicles and roads, intelligent traffic control center can centralize statistical processing and trend prediction of road network information within the whole city, to release traffic information to relevant vehicles and traffic flow, and carry out real-time scheduling such as signal adjustment, road dynamic speed limit, and path induction operations, to ensure the smooth operation of urban road traffic flow, effectively respond to unexpected accidents, and reduce congestion [5]. The data communication of such applications is mostly unicast, and the transmission form is multihop transmission between vehicles, and the delay requirements vary according to the nature of specific types; for example, video and audio conferencing have high delay requirements, while information pushing has lower requirements
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