Research on Multi-Objective Optimization Method of Edge Cloud Computing Virtual Machine Placement

Abstract

Abstract With the emergence of demand for massive computing tasks in the edge cloud of the city, the disordered computing in the edge cloud leads to the high energy consumption of CPU computing and the problem of too long time delay caused by the blockage of computing tasks. This has become the first technical difficulty to solve in the construction of edge cloud. The virtual machine placement method is optimized by computing energy consumption and computing delay. First, the LRR physical host screening model is constructed to detect the status of the physical hosts and form a list of migrated physical hosts; secondly, the MMT time scale model is constructed to generate the list of migrated virtual machines; finally, the GA algorithm is used to place the virtual machines. The simulation results show that this algorithm can reduce the CPU energy consumption of the edge cloud center by 20. 21% and the time delay by 16. 11%. This optimization method has a good theoretical guidance effect on the construction of cloud computing.