Joint Optimization of Task Offloading and Service Placement for Digital Twin empowered Mobile Edge Computing

Mobile edge computing (MEC) can enhance application performance effectively by offloading computation tasks to the edge server hosting corresponding service via multi-access wireless networks. However, existing service placement policies are more based on the assumption that application services can be used without restrictions, while ignoring the constraints of software usage by license, which always limits user number, usage periods, etc. To address these challenges, in this paper, we introduce an architecture of digital twin-empowered MEC with good scalability and reliability, formulate an optimal problem by jointly optimizing task offloading and service placement, which takes into account the usage number limitation for one service at the same time. To tackle this mix integer non-linear programming problem (MINLP), we propose a DRL-based algorithm JTOSP to deal with high-dimensional input data from MEC system, and to cope with the stochastic nature in dynamic underlying network efficiently. Numerical experiments are conducted and the simulation results show that our algorithm outperform other algorithms and reduce energy consumption efficiently.