Research on Fog Computing Resource Allocation Based on Fusion Optimi-zation Algorithm of GWO and PSO
In response to the resource allocation problem in fog computing,the paper proposes a new resource allocation approach by combining the excellent global search capability of Grey Wolf Optimization(GWO)algorithm with the good algorithm convergence capability of Parti-cle Swarm Optimization(PSO)algorithm.In addition,the weight values of the optimization al-gorithm have a significant impact on the algorithm performance.The paper introduces an adap-tive weight strategy to adjust the algorithm weights,optimizing the accuracy and efficiency of the algorithm for node resource allocation.Experimental results show that the proposed algo-rithm has better performance in fog computing resource allocation problems,providing a more efficient and rapid resource scheduling strategy for tasks.
Fog computingResource allocationGWOPSOAdaptive weight strategy
万方数据
维普
