Research and Simulation Implementation of Fog Calculation Resource Allocation Algorithm

In recent years, with the rapid development of big data artificial intelligence, automatic driving and other fields, traditional cloud computing has been unable to meet the actual application needs. In order to solve the problem of insufficient resources and practical application requirements, in 2011, the concept of fog computing should be carried out. Health. In this paper, based on the shortcomings of fog computing in traditional resource allocation algorithm (genetic algorithm, simulated annealing algorithm), a genetic algorithm based on Min-Min and a simulated annealing algorithm based on hopping cooling criterion are proposed. The two algorithms are organically combined to increase understanding. The search range of space avoids the defect that the traditional algorithm is easy to fall into the local optimum, and avoids the problem that the annealing algorithm has too many convergence times. The simulation results show that under the algorithm, the user's QoS is improved by a large program and is effective and reduces latency and execution costs during task execution.