E-commerce cloud computing data migration method based on improved slime mould algorithm

Abstract

The inherent dynamism of e-commerce cloud environments, characterised by massive data volumes and high-concurrency demands, poses significant challenges to traditional data migration approaches. For this reason, this paper firstly improves the sticky mushroom algorithm (SMA) (BOSMA) by replacing the anisotropy operator of the SMA with a balanced optimisation operator, and adding a stochastic difference variance operator to the SMA to avoid premature convergence. To reduce the migration energy consumption, the e-commerce cloud computing data migration task dependency graph is designed, and the objective function to lower the energy consumption during migration is constructed. The BOSMA is adopted to discover the finest solution to the target function to acquire the migration of the task with the largest reduction in energy consumption. The simulation outcome implies that the BOSMA method can quickly search for solutions with less migration energy consumption.