| In recent years,with the rapid development of information and communication technology in the field of mobile communication,the modern life style has changed greatly.People expect to exchange data anytime and anywhere in the mobile vehicles.However,due to some practical factors(for example,the increase of vehicle density on the road),the current cellular network can not effectively support the growing service requests and the generated data traffic without reducing the quality of service.The Internet of vehicles based on mobile edge computing is envisioned as a potential solution to meet the application needs.However,MEC resources are limited.At the same time,considering the complex network environment of the Internet of vehicles,many problems such as task decision-making and resource allocation become the key to restrict the scalability and network improvement of MEC.In conclusion,considering the limitation and heterogeneity of resources,the optimization of heterogeneous resources based on MEC in the Internet of vehicles is studied.The main work includes the following two aspects:1.Aiming at the resource optimization problem based on MEC multi server in the Internet of vehicles,the optimization problem is formulated to maximize the average system benefit by combining task offloading and resource allocation strategies.The limitation of resources,the heterogeneity and diversity of tasks are considered.In view of the complexity of solving the problem,the original optimization problem is first decomposed,then the resource allocation problem is solved,and a multi wheel combined offloading scheduling mechanism is proposed to solve the task offloading problem.The mechanism realizes the system to maximize the average system benefit while ensuring that the vehicle benefit will not be reduced.Finally,the simulation results show the effectiveness of the proposed scheme.2.Aiming at the resource optimization problem based on MEC cache service in the Internet of vehicles,a MEC cache service scenario is established.The strategies of computing offloading,cache and resource allocation are jointly considered to minimize the total delay consumption.Because the problem is a mixed integer nonlinear optimization problem,the generalized benders decomposition method is adopted andimproved to solve it effectively.Finally,the simulation results show that the effectiveness of the scheme is proved both in running time and total system delay consumption. |
