@article{Tian2026, 
author = {Yujie Tian and Ming Zhu and Jing Li and Cong Liu and Ziyang Zhang},
title = {A Workflow Scheduling Method Based on the Combination of Tunicate Swarm Algorithm and Highest Response Ratio Next Scheduling},
year = {2026},
journal = {Computers, Materials & Continua},
volume = {87},
number = {2},
pages = {84},
keywords = {Workflow scheduling, cloud computing, tunicate swarm algorithm, highest response ratio next scheduling},
url = {https://www.sciopen.com/article/10.32604/cmc.2026.075063},
doi = {10.32604/cmc.2026.075063},
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.}
}