Development an intelligent task scheduling method in heterogeneous distributed information systems

Authors

DOI:

https://doi.org/10.15587/1729-4061.2025.329263

Keywords:

distributed computing systems, graph models, resource planning, intelligent management systems

Abstract

The object of this study is the task scheduling process in heterogeneous distributed information systems. The scientific task addressed relates to the low efficiency of resource management, especially under conditions of dynamic workload and significant uncertainty, which are typical for distributed information systems. An intelligent task scheduling method has been devised for heterogeneous distributed information systems, which effectively combines DAG (Directed Acyclic Graph) and GERT (Graphical Evaluation and Review Technique) models with advanced artificial intelligence algorithms. The proposed method employs a Graph Attention Network (GAT) to account for probabilistic dependences between tasks and Proximal Policy Optimization (PPO) for dynamic control of task distribution within the system. Furthermore, a Bayesian method is used to optimize the assignment of tasks to computing nodes. The use of the proposed method reduced the average task execution time from 51.5 to 35.2 seconds, and the standard deviation of the load between nodes from 0.47 to 0.22.

These results are explained by the flexibility of the models to unforeseen changes and the ability to self-learn based on accumulated data. A feature of the method is the combination of classical graph models with probabilistic estimation and adaptive AI mechanisms, which made it possible not only to take into account the dynamics of the environment but also to ensure accurate response to changes in resource availability. By using GERT graphs, the algorithm forms alternative planning paths in case of failures or unforeseen delays, and machine learning components provide self-correction of decisions. The method is oriented towards application in cloud and IoT infrastructures, in which scalability, planning accuracy, and resilience to changes are critical

Author Biographies

Serhii Yenhalychev, Simon Kuznets Kharkiv National University of Economics

PhD Student

Department of Cybersecurity and Information Technologies

Oleksii Leunenko, Simon Kuznets Kharkiv National University of Economics

PhD Student

Department of Cybersecurity and Information Technologies

Viacheslav Davydov, Science Entrepreneurship Technology University

Doctor of Technical Sciences, Associate Professor

Department of Information Technology and Cyber Security

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Development an intelligent task scheduling method in heterogeneous distributed information systems

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Published

2025-06-25

How to Cite

Yenhalychev, S., Leunenko, O., & Davydov, V. (2025). Development an intelligent task scheduling method in heterogeneous distributed information systems. Eastern-European Journal of Enterprise Technologies, 3(9 (135), 6–18. https://doi.org/10.15587/1729-4061.2025.329263

Issue

Vol. 3 No. 9 (135) (2025): Information and controlling system

Section

Information and controlling system

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Copyright (c) 2025 Serhii Yenhalychev, Oleksii Leunenko, Viacheslav Davydov

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