A task offloading algorithm for cloud-edge collaborative system based on Lyapunov optimization.

Due to the limitation of computing resources and storage resources, mobile edge computing cannot cope with the massive data generated by the Industrial Internet of Things (IIoT). However, traditional mobile cloud computing has rich computing resources. Therefore, through the construction of cloud computing and edge computing collaborative system, high bandwidth and low latency network services for the Internet of things can be provided. Based on Lyapunov optimization theory, the resource allocation and power consumption in cloud-edge collaborative system are investigated in this paper. Firstly, a cloud-edge collaboration architecture is proposed, then by establishing the dynamic queue model of cloud computing server and edge computing server, and combining with the system power function to form a drift plus penalty function framework, the problem is reduced to a constrained optimization problem. Finally, the offloading algorithm based on congestion is given. The simulation results show that the proposed optimization scheme can effectively reduce the overall power consumption and congestion of cloud-edge collaborative system. [ABSTRACT FROM AUTHOR]