@Article{cmc.2026.075063,
AUTHOR = {Yujie Tian, Ming Zhu, Jing Li, Cong Liu, Ziyang Zhang},
TITLE = {A Workflow Scheduling Method Based on the Combination of Tunicate Swarm Algorithm and Highest Response Ratio Next Scheduling},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {87},
YEAR = {2026},
NUMBER = {2},
PAGES = {--},
URL = {http://www.techscience.com/cmc/v87n2/66601},
ISSN = {1546-2226},
ABSTRACT = {Workflow scheduling is critical for efficient cloud resource management. This paper proposes Tunicate Swarm-Highest Response Ratio Next, a novel scheduler that synergistically combines the Tunicate Swarm Algorithm with the Highest Response Ratio Next policy. The Tunicate Swarm Algorithm generates a cost-minimizing task-to-VM mapping scheme, while the Highest Response Ratio Next dynamically dispatches tasks in the ready queue with the highest-priority. Experimental results demonstrate that the Tunicate Swarm-Highest Response Ratio Next reduces costs by up to 94.8% compared to meta-heuristic baselines. It also achieves competitive cost efficiency vs. a learning-based method while offering superior operational simplicity and efficiency, establishing it as a highly practical solution for dynamic cloud environments.},
DOI = {10.32604/cmc.2026.075063}
}