Resource Allocation In Internet Of Vehicular Communication

The internet of vehicles attracts more and more attention as one of the promising applications in future intelligent transportation communication systems.However,the increasing number of vehicles has severely challenged the communication quality and limited resources in the Internet of Vehicles.Both the access links selection and corresponding resource allocation are the key issues to the performance optimization.With the optimization goals of improving system throughput,spectrum utilization,and energy efficiency,this thesis focuses on the offloading strategy and resource allocation algorithm under the conditions of low latency and high reliability.Firstly,this thesis presents a single-layer and multi-layer heterogeneous network scenarios which suffers from a fast fading channel caused by high-speed mobility in IoV In the single-layer IoV network,the impact of mobility to the resource management is investigated in terms of data transmission reliability.According to the multi-slot model,the change characteristics of the channel state over a period of time can be predicted,and then the corresponding resource allocation is made.By establishing a related mathematical model and theoretical analysis of the model,a low complexity sub-optimal power allocation algorithm is proposed.Secondly,this article builds an offloading framework based on Mobile Edge Computing(MEC)to solve the problem of high latency in cloud computing.The calculation offloading task can be offloaded to the MEC server,or it can be offloaded to local processing.In this scenario,a joint calculation offloading and resource allocation algorithm is proposed in this paper.First,a resource optimization model that minimizes the system average delay as a utility function is established.Second,the Cross-Entropy(CE)algorithm is used to obtain the offloading strategy.Then according to the obtained offloading strategy,the channel and MEC server computing resources are allocated using the Gale-Shapley(GS)algorithm.In addition,we have introduced a multi-slot mode,which means that there will be a switching delay if the offload mode changes between two consecutive time slots.In addition,based on the cooperation between the roadside unit and the base station,this paper proposes a resource allocation scheme based on Markov Decision Process(MDP),which maximizes the overall system benefit.The benefits of the system include revenue,costs,and available resources.After defining the system's state space,action space,revenue function,and transition probability distribution,the optimization problem is formulated as a Markov decision process.In order to solve the proposed Markov process,we use an iterative algorithm to obtain the optimal solution,that is,the action that should be taken in a specific system state.Simulation results show that the performance improvement can be achieved through MDP-based schemes within acceptable complexity.