A Workflow Scheduling Method Based on the Combination of Tunicate Swarm Algorithm and Highest Response Ratio Next Scheduling

Yujie Tian¹, Ming Zhu¹, Jing Li^1,*, Cong Liu², Ziyang Zhang¹
1 School of Computer Science and Technology, Shandong University of Technology, Zibo, China
2 NOVA Information Management School, Universidade Nova de Lisboa, Campus de Campolide, Lisboa, Portugal
* Corresponding Author: Jing Li. Email: email

Computers, Materials & Continua https://doi.org/10.32604/cmc.2026.075063

Received 24 October 2025; Accepted 16 January 2026; Published online 13 February 2026

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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.

Keywords

Workflow scheduling; cloud computing; tunicate swarm algorithm; highest response ratio next scheduling

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A Workflow Scheduling Method Based on the Combination of Tunicate Swarm Algorithm and Highest Response Ratio Next Scheduling

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