Research On Lyapunov-based Heterogeneous Resources Optimization In IoV

In recent years,with the rapid development of Internet of Vehicle(Io V),some timesensitive technologies such as autonomous driving,vehicle navigation have emerged.Due to the limited computing resources of mobile vehicles,they can not fully meet the needs of above services.Mobile Edge Computing(MEC)technology extends computing and storage resources to the edge of the network and can reduce the processing delay of tasks.Therefore,MEC technology can provide low-latency and high-utility vehicular services.However,owing to the limited computational resources of MEC,the influence of the rapid fluctuation of wireless channels,and the randomness of the moving direction and speed of vehicles,the resource scheduling problem becomes very complicated and challenging.Aiming at the above shortcomings,this thesis mainly studies the heterogeneous resource optimization problem based on Lyapunov theory in the dynamic environment of the vehicular networks.The thesis focuses on two main aspects as follows:1.In order to solve the problems of service discontinuity and poor Qo E caused by the malfunction of BS,take into account the two situations that the BS can provide services(i.e.,vehicles are online)and the BS cannot communicate in emergencies(i.e.,vehicles are offline),then allocate and manage the communication resources and computing resources in the system.The online vehicles upload a part of task to MEC server for calculation through the V2I(Vehicle-to-Infrastructure)technology,then use Lyapunov algorithm to decouple the random optimization problem into independent optimizations for each frame,construct a penalty drift function,and minimize the upper bound of the drift and penalty function.Finally,the optimal allocation of frequency of CPU cycles,transmission power and bandwidth of the moving vehicles are obtained.When the vehicles are offline,multi-hop routing algorithm is adopted to obtain the optimal path through V2V(Vehicle-to-Vehicle)technology to offload the computing tasks.Simulation results show that the proposed scheme can maintain reliable communication and maximize the communication capacity of the system.2.Aiming at the problem of low resource utilization rate due to the random change of speed and communication channel in the dynamic environment of the vehicular networks.Firstly,the non-orthogonal multiple access technology is introduced into the vehicular edge computing networks,then,a resource optimization scheme based on nonorthogonal multiple access is proposed,which not only solves the problem of insufficient wireless communication resources between multiple vehicles and base stations,but also reduces the energy consumption of the system.Next,an optimization algorithm based on Lyapunov theory is designed to minimize the average energy consumption,which formulates an optimal offloading and caching strategy for vehicle users.Finally,the simulation results show that the proposed scheme can effectively improve the utility of resources compared with the existing schemes.