Hamzeh Aljawawdeh
Simplifying microservices migration with advanced genetic algorithms
Aljawawdeh, Hamzeh; Abuezhayeh, Sami; Qaddoumi, Eman; Maghrabi, Louai
Authors
Sami Abuezhayeh
Eman Qaddoumi
Louai Maghrabi
Contributors
Azzam Hannoon
Editor
Abdullah Mahmood
Editor
Abstract
The increasing complexity and size of software systems have revealed the limitations of monolithic architectures, leading to the adoption of microservices as a more flexible, scalable, and maintainable alternative. This paper introduces an innovative approach to microservices identification and migration from monolithic architecture using advanced multi-objective genetic algorithms. By formulating the microservices identification problem as a multi-objective Optimization task, we harness the power of genetic algorithms to search for Pareto-optimal solutions, ultimately leading to an efficient decomposition of monolithic systems. Our proposed methodology offers a systematic approach to the migration process, ensuring minimal downtime and maximum efficiency. We present real-world case studies showcasing our approach’s successful application alongside examining its limitations and future research directions. This work encourages further exploration and application of multi-objective genetic algorithms in software engineering and system architecture, ultimately simplifying the transition from monolithic to microservices architectures.
Online Publication Date | Nov 9, 2023 |
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Publication Date | Nov 9, 2023 |
Deposit Date | Nov 25, 2023 |
Publisher | Springer Verlag |
Pages | 441-452 |
Series Title | Studies in Computational Intelligence |
Book Title | Artificial Intelligence, Internet of Things, and Society 5.0 |
ISBN | 9783031432996 |
DOI | https://doi.org/10.1007/978-3-031-43300-9_36 |
Public URL | https://uwe-repository.worktribe.com/output/11462673 |
Publisher URL | https://doi.org/10.1007/978-3-031-43300-9_36 |
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