Research On Offloading Strategy Of Mobile Edge Computing For Low Earth Orbit Satellite

At present,the 5th Generation(5G)mobile communication network has been put into commercial use,and the research of the 6th Generation(6G)mobile communication network has been carried out in the academic world.6G has the characteristics of wide-area coverage and will cover remote areas such as deserts,forests,and oceans.It is expected to realize the vision of seamless global coverage.On the other hand,for 6G,whether it is hotspot area or sparse area of the communication service,the computing requirements of the service generally exist.However,the deployment of terrestrial networks is restricted by economic benefits and technology,so that the needs of remote areas cannot be met.At this time,the Mobile Edge Computing(MEC)of low-orbit satellite is particularly important,so in recent years,it has gained a lot of attention in the academic and industrial circles.The deployment of MEC server on Low Earth Orbit(LEO)satellite increases satellite launch cost and energy consumption during satellite operation.Therefore,when studying the LEO satellite MEC computation offloading problem,facing many challenges: MEC computing resource management?task scheduling?system energy consumption ? user Quality of Experience(Qo E)requirements and application partitioning.This paper focuses on the problem of computation offloading in the Single Access-Mobile Edge Computing(SA-MEC)scenario.Firstly,two sub-scenarios of "light load" and "heavy load" in the SA-MEC scenario are defined,and then the computation offloading problems of these two sub-scenarios are studied respectively.1.Facing the "light load" sub-scenario,firstly,a system cost model of latency and energy consumption was established to address the challenges of task scheduling?MEC computing resource management and system energy consumption.Secondly,in order to reduce the complexity of the model,a Joint Computation Offloading and Resource Allocation Strategy based on Game Theory(JCORAS-GT)is proposed.This solves the problem of the offloading strategy with optimal resource allocation and the problem of optimal uplink and downlink communication and computing resource allocation with predetermined offloading strategy.Finally,The simulation results show that the JCORAS-GT strategy can effectively reduce the cost of the system.2.Facing the "heavy load" sub-scenario,firstly,the challenge of user Qo E requirements are major based on “light load” sub-scenario.A system cost minimum model based on queuing theory is established.This model can meet the different needs of various types of tasks for latency and energy consumption.Secondly,a computation offloading strategy based on improved ant colony algorithm(COS-IACA)is proposed which not only reduces the cost of local computation through the local resource allocation,but also employs the ant colony algorithm to find the optimal queuing order for offloading tasks to reduce the system cost on the LEO satellite.Finally,it is verified by simulation that the proposed algorithm can effectively reduce the cost of the system.