Joint Computation and Communication Resources Allocation in Industrial Internet of Things with Edge Computing
Mingyue Sun, Zhenghang Lian, Yazhou Yuan, Kai Ma, Xiaoyuan Luo · 2023
As the scale and functional capabilities of Industrial Internet of Things (IIoT) deployments continue to expand, the amount of data at the device end on the field site is growing exponentially, which leads to unreliable communication quality and limited network resources. To improve the performance of the communication network, this paper proposes a cloud-edge-end three-layer communication architecture that integrates edge computing technology (ECT) with cooperative communication technology. Edge servers (ES) with computing capabilities are deployed in the factory as data forwarding relays to reduce the packet loss rate of the communication network. Under the constraints of communication resources, a bandwidth release model is established to analyze the mapping relationship between computing power and bandwidth. In addition, we adopt the Stackelberg game to characterize the interaction between the factory and the ES, and construct an optimization problem that maximizes the factory utility under the constraint of the total amount of network resources. Finally, a distributed iterative algorithm based on the backward induction method is used to achieve the joint optimization allocation of computing power and bandwidth. Simulation results demonstrate that the proposed solution can effectively allocate resources and improve the overall efficiency of the factory.