A Research Of Computation Offloading And V2V Resource Allocation Based On Vehicular Fog Computing Architecture

For the vehicular network,people paid more attention to the safety application in the early stage.Recently,with the development of 5G communication technology and diversity of business needs,vehicular network has generated more possibilities to support more non-secure applications,such as advertising,social application,multimedia entertainment and so on.However,the consequent huge amount of data and computation will bring a heavy burden to the network.Some studies have suggested that the vehicular network technology and fog computing can be combined to form vehicle fog computing and move down the storage and calculation,thereby reducing the burden on the network.The development of fog computing originates from the increasingly powerful functions of various of access devices.By transfering the computing service function from the cloud to the access layer,that is,the fog end,the access devices can use the remaining computing resource to provide service,thereby reducing the load of core network,improving response speed and so on.In fog computing,handheld devices are generally not considered as a server due to the weak performance.Otherwise,in vehicle fog computing,with sufficient energy and better heat dissipation,the performance and power consumption of the in-vehicle devices can be far greater.The vehicle can be either a computing service requester or a server,which is different from fog computing.For this reason,the research results of fog computing can not be directly used in vehicle fog computing,so this thesis will carry out research on vehicle fog computing and related issues.In order to minimize the hardware deployment cost of vehicle fog computing infrastructure and reduce the implementation difficulty,this thesis designs the infrastructure of vehicle fog computing based on the standard 5G access network.Through the discussion of this infrastructure,this thesis analyzes the key issues of vehicle fog computing,which include distance prediction,vehicle to vehicle(V2V)computation offloading and V2 V communication resource allocation.This thesis analyzes the distance prediction problem designs a distance prediction algorithm in vehicular network based on the well-known data fusion algorithm Kalman filter.This thesis analyzes the V2 V computation offloading problem and mathematically models it.In order to meet the real-time demand of vehicle fog computing decision,a Heuristic algorithm based on Clustering Dynamic Programming(HCDP)is designed to solve the V2 V computation offloading problem.This thesis analyzes the V2 V communication resource allocation problem and designs an improved TID(ITID)algorithm based on the Toledrant Interference Degree(TID)algorithm proposed in the existing research results to achieve higher communication resource utilization rate.Finally,this thesis designs the simulation scenarios of V2 V computation offloading and V2 V communication resource allocation problem.The simulation result shows that HCDP algorithm and ITID algorithm have excellent performance under different load scenarios.