Research On Incentive Mechanism And Transmission Decision For Content Delivery In C-V2X Networks

The continuous development of vehicular networks has improved traffic safety and driving efficiency.The emergence of new services such as autonomous driving,long-distance driving,and real-time road information acquisition have put forward higher requirements on data transmission rate and communication reliability.Cellular vehicular networks have attracted wide attention from industry and academia due to wide coverage,low latency,and high reliability.By caching a part of popular contents to vehicles,the content distribution among vehicles can effectively reduce transmission latency and improve network throughput.Currently,researchers have conducted a lot of research on collaborative content distribution in cellular vehicular networks.When a vehicle participates in content distribution,it consumes its limited resources.In order to ensure their own interests,rational vehicles may refuse to participate in collaborative content distribution,which results in poor system performance.Considering the highly dynamic nature of the Internet of Vehicles,how to design an effective incentive mechanism for content distribution is an important issue to be resolved.In addition,in a dense environment,a vehicle may receive multiple content distribution requests at the same time.How to design a reasonable transmission decision mechanism in a high-speed environment to satisfy the content distribution requests of multiple vehicles also requires in-depth research.The main work of this thesis is as follows:An incentive mechanism based on dynamic pricing is proposed.First,the factors that affect the content distribution among vehicles are given,including the content popularity,the content size,the link transmission rate,and the link interruption probability.Taking into account the different dimensions and ranges of different factors,these factors are normalized,and then integrated to the incentive value that vehicles can obtain by assisting content distribution in a dynamic vehicular environment.Then,with the goal of maximizing revenue,a mathematical model is established and solved,and a corresponding content distribution strategy is proposed.A cache content replacement strategy is designed based on the incentive mechanism.According to the incentive income obtained by vehicles through participating in content distribution in the historical records,a revenue prediction problem based on multi-factor stock selection model is established,and the content with higher potential revenue will be cached to further increase the opportunities for vehicles to participate in content distribution and ensure the long-term revenue of vehicles.Simulation results show that the proposed incentive mechanism and cache content replacement strategy effectively improve the content delivery ratio and cache hit ratio in vehicular networks.A transmission decision mechanism with optimal energy efficiency is proposed.When multiple vehicles initiate multiple video content distribution requests at the same time,the transmission decision problem of the content providing vehicle is modeled.Considering that the processing capabilities of vehicles in the network are heterogeneous,and the channel conditions of the vehicles in the highly dynamic environment are also quite different,video transcoding technology is introduced.In order to ensure the benefits of the vehicles which provide video content and improve the service quality of the system,the transmission energy efficiency of content distribution requests is proposed as an optimization goal,that is,to meet the most content distribution requests with minimum video transcoding and transmission energy consumption.Specific implementation algorithms are designed in centralized and distributed scenarios.In the centralized scenario,the macro base station acts as a centralized control center,collecting information on all content-providing and content-requesting vehicles in the coverage area,and using Hungarian algorithms to achieve vehicle-to-vehicle matching in polynomial time.In the distributed scenario,with the help of information exchange between neighboring vehicles,a distributed algorithm based on the greedy idea is proposed,and the collaborative decision between vehicles is realized with lower complexity.Simulation results show that the proposed transmission decision mechanism can effectively reduce the overall transmission energy consumed in the system and improve the completion rate of video content distribution requests.