Title: Multi-objective workflow scheduling in the cloud environment based on NSGA-II

Authors: Tingting Dong; Chuangbai Xiao

Addresses: School of Computer and Artificial Intelligence, Beijing Wuzi University, Tongzhou, Beijing, China; Faculty of Information Technology, Beijing University of Technology, Chaoyang, Beijing, China ' Faculty of Information Technology, Beijing University of Technology, Chaoyang, Beijing, China

Abstract: The emergence of cloud computing offers a novel perspective to solve large-scale computing problems. Workflow scheduling is a major problem in the cloud environment, and parallelism and dependency are two important characteristics of tasks in a workflow, which increases the complexity of the problem. Workflow scheduling is also a multi-objective scheduling problem, and task execution time and cost are the two extremely significant goals for users and providers in the cloud environment. Existing heuristic algorithms are popular, but they lack robustness and need to be revised when the problem statement changes. Evolutionary algorithms have a complete algorithm system, which is widely used in the multi-objective scheduling problem. In this paper, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is utilised to solve the workflow scheduling problem aiming at minimising the task execution time and cost. Some real-world workflows are used to make simulation experiments, and comparative simulations with genetic algorithm are given. Results show that NSGA-II is effective for the workflow scheduling.

Keywords: cloud computing; workflow scheduling; NSGA-II; non-dominated sorting genetic algorithm-II; multi-objective scheduling.

DOI: 10.1504/IJWMC.2026.150837

International Journal of Wireless and Mobile Computing, 2026 Vol.30 No.1, pp.106 - 112

Received: 20 Jan 2021
Accepted: 25 May 2021
Published online: 24 Dec 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article