Joint Pricing, Server Orchestration and Network Slice Deployment in Mobile Edge Computing Networks

The integration of mobile edge computing (MEC) and network slicing can provide low-latency and customized services. In such integrated wireless networks, we propose a pricing-driven joint MEC server orchestration and network slice deployment scheme (PD-JSOSD), jointly solving the pricing, MEC server orchestration and network slicing deployment issues. We divide the system into an infrastructure provider layer (IPL), network planning layer (NPL) and resource allocation layer (RAL), and a three-stage Stackelberg game is proposed to describe their relationships. To obtain the Stackelberg equalization, we propose a three-layer deep reinforcement learning (DRL) algorithm. Specifically, the dueling double deep Q-network (D3QN) is used in the IPL, and the DRL with branching dueling Q-network (BDQ) is used in the NPL and the RAL to cope with the large-scale discrete action spaces. Moreover, we propose an innovative illegal action modification algorithm to improve the convergence of the BDQ. Simulations verify the convergence of the three-layer DRL and the superiority of modified-BDQ in dealing with large-scale action spaces, where modified-BDQ can improve the convergence by 21.9% and 28.3%. Furthermore, compared with the benchmark algorithms, JSOSD in the NPL and the RAL can improve system utility by up to 52.1%, proving the superiority of the server orchestration and slice deployment scheme.