Efficient Fog Node Resource Allocation Algorithm Based on Taboo Genetic Algorithm

In the fog computing network, in order to improve user task execution efficiency under resource constraints, this paper proposes an efficient fog node resource allocation algorithm based on Taboo genetic algorithm. First, the resource constraint problem is modeled as a communication resource constraint and a computing resource constraint problem, and the performance constraint problem is modeled as a task execution delay constraint problem. Secondly, the advantages of taboo genetic algorithm are analyzed, and key processes such as chromosome coding, fitness function, selection process, taboo crossing process, and taboo mutation process are designed. Finally, an efficient fog node resource allocation algorithm based on Taboo genetic algorithm is proposed. In the experimental part, from the two aspects of the number of different tasks and the number of different fog nodes, it is verified that the algorithm in this paper significantly reduces the execution time of user tasks.