Research On Service Chain Migration Scheduling In Internet Of Vehicles

With the rapid development of Internet of Vehicles(Io V)technology,emerging onboard application services continue to emerge,leading to a sharp increase in data at the edge of the network.However,uploading massive data related to on-board application services to the remote cloud for analysis and processing is easy to cause core network congestion,resulting in high time delay,and it is difficult to guarantee the real-time performance of onboard application services.In order to cope with the above challenges,Mobile Edge Computing(MEC)emerged as a new network paradigm,providing remote cloud computing and storage capacity at the edge of wireless access network,effectively ensuring the reliability of communication and reducing service response delay.The current research on service caching mainly focuses on independent services rather than those with dependent relationships.Therefore,it is very necessary to study how to deploy the service chain of the remote cloud to different edge nodes and how to schedule workload between edge nodes that have cached the same service.First,complex application services with dependencies are modeled as service chains.Secondly,the service chain processing process is modeled as an open markov queuing network,and combined with the queuing model to analyze the average stay delay generated by the service chain processing tasks,a mixed integer nonlinear programming mathematical model is established.Finally,with the Outer Approximation(OA)algorithm,a scheduling strategy based on service chain cache and workload scheduling is proposed to solve the mixed integer linear programming problem.The influence of the task arrival rate,storage capacity and other influencing factors on the service response delay was investigated.The simulation results show that it can effectively reduce the average service response delay and improve the resource utilization rate of edge nodes.Figure 21;Table 6;Reference 63...