An enhanced dung beetle optimizer for cloud task schedule

Abstract

Aiming to address the shortcomings of Dung Beetle Optimizer (DBO) in the areas of accuracy and convergence speed in dealing with cloud computing task scheduling issues, this paper suggests an advanced Dung Beetle Optimizer (DGTDBO)based cloud computing task scheduling method by combining the differential strategy and the perturbation strategy. Among them, the differential strategy strengthens the global exploration performance of the method, while the perturbation strategy improves the capability of the algorithm to escape from the local optimal trap. Through validation on different sizes of cloud computing systems, it is confirmed that the suggested DGTDBO can enhance the solution accuracy and speed of the algorithm effectively. It is considered as a promising cloud scheduling method.