Integrating Multi-access Edge Computing(MEC) in Low Earth Orbit(LEO) network is an important way to provide globally seamless low-delay service. In this paper, we consider the scenario that MEC platforms with computat...Integrating Multi-access Edge Computing(MEC) in Low Earth Orbit(LEO) network is an important way to provide globally seamless low-delay service. In this paper, we consider the scenario that MEC platforms with computation and storage resource are deployed on LEO satellites, which is called "LEO-MEC". Service request dispatching decision is very important for resource utilization of the whole LEO-MEC system and Qo E of MEC users. Another important problem is service placement that is closely coupled with request dispatching. This paper models the joint service request dispatching and service placement problem as an optimization problem, which is a Mixed Integer Linear Programming(MILP). Our proposed mechanism solves this problem and uses the solved decision variables to dispatch requests and place services. Simulation results show that our proposed mechanism can achieve better performance in terms of ratio of served users and average hop count compared with baseline mechanism.展开更多
基金funded by the Excellent Postdoctoral Study Project Funding of Hebei Province,grant number B2019005006。
文摘Integrating Multi-access Edge Computing(MEC) in Low Earth Orbit(LEO) network is an important way to provide globally seamless low-delay service. In this paper, we consider the scenario that MEC platforms with computation and storage resource are deployed on LEO satellites, which is called "LEO-MEC". Service request dispatching decision is very important for resource utilization of the whole LEO-MEC system and Qo E of MEC users. Another important problem is service placement that is closely coupled with request dispatching. This paper models the joint service request dispatching and service placement problem as an optimization problem, which is a Mixed Integer Linear Programming(MILP). Our proposed mechanism solves this problem and uses the solved decision variables to dispatch requests and place services. Simulation results show that our proposed mechanism can achieve better performance in terms of ratio of served users and average hop count compared with baseline mechanism.
