Abstract:

[Objective] Under the background of the computational power network, this paper studies the energy consumption of multi-user and multi-server edge computing systems, and further realizes the energy consumption optimization of edge computing systems by offloading computing tasks and dynamic resource scheduling among multiple edge servers. [Methods] First, an edge computing system and scheduling system including multi-user and multi-server are established, the key factors affecting the energy consumption of the system are analyzed, and the terminal transmission power and the clock frequency of the edge server are optimized according to the actual computing power requirements. On this basis, a dynamic scheduling strategy for computing tasks among multiple edge servers is designed to avoid the problem of energy waste caused by the uneven load. [Results] The correctness of the method is proved by theoretical derivation. Based on the simulation model and strategy design, it is verified that the method in this paper can realize the sharing of computing resources and reduce the energy consumption level while ensuring service quality. [Limitations] In this paper, the method is mainly analyzed from the perspectives of calculation and data transmission, the relevant model is reasonably simplified and analyzed, and the dimensions of network, application and data security are comprehensively considered on the current basis, and the implementation practice is carried out, which can further improve the application value of the method. [Conclusions] Based on the unified management and scheduling capabilities of resources in the computational power network, reasonable resource management, computing task offloading, and task scheduling are carried out in edge computing and other scenarios, which can effectively improve service-oriented QoS assurance and energy consumption optimization for underlying resources.

Key words: computational power network, edge computing, energy-efficiency optimization