In view of the fact that enterprises can improve productivity through workflows, the problem of huge number of multi-user workflows and unbalanced user load on cloud computing platforms is investigated, based on an ant colony algorithm for decision task optimisation. With the help of a colony intelligence algorithm, automatic scheduling of tasks and optimisation of resources are accomplished while satisfying the enterprise's needs, while meeting server time constraints and load balancing. The optimised cloud workflow scheduling algorithm builds an intelligent business system that is highly flexible and scalable, and three times faster in terms of processing speed than before the optimisation.

Yongqiang Li, Da Chen, Junjie Hao. Cloud workflow scheduling optimization research based on ant colony algorithm. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 5: 9-13. https://doi.org/10.25236/AJCIS.2023.060502.

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