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Journal of Computational Social Dynamics

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Published

2023-11-28

Issue

Vol. 8 No. 11 (2023): Journal of Computational Social Dynamics-November-2023

Section

Articles

How to Cite

Ramamoorthi, V. (2023). AI-Driven Partitioning Framework for Migrating Monolithic Applications to Microservices. Journal of Computational Social Dynamics, 8(11), 63–72. Retrieved from https://vectoral.org/index.php/JCSD/article/view/131

AI-Driven Partitioning Framework for Migrating Monolithic Applications to Microservices

Vijay Ramamoorthi

Independent Researcher

Keywords: Microservices, Microservice architecture, Neuromorphic AI integration, CARGO framework System Dependency Graphs

Abstract

Microservice Architecture (MSA) has become a standard for designing scalable and flexible enterprise applications. However, the process of migrating monolithic systems to microservices is fraught with challenges, including the risk of creating distributed monoliths and managing complex distributed transactions. To address these issues, we present CARGO (Context-sensitive lAbel pRopaGatiOn), an AI-guided framework that improves microservice partitioning through the use of System Dependency Graphs (SDGs) and a context-sensitive label propagation algorithm. SDGs enable detailed modeling of both intra-service and inter-service dependencies, capturing critical aspects like call-return, data, heap, and transactional edges. By iteratively refining partition boundaries, CARGO minimizes inter-service coupling, reduces the occurrence of distributed transactions, and enhances service cohesion. Evaluations conducted on benchmark applications such as Daytrader and JPetStore demonstrate that CARGO significantly outperforms state-of-the-art tools like Mono2Micro and CoGCN in terms of transaction purity, latency, throughput, and architectural quality. This work establishes a foundation for automating the migration of monolithic applications into efficient, scalable microservice architectures and opens avenues for applying CARGO to other programming environments like Python and .NET.

Author Biography

Vijay Ramamoorthi, Independent Researcher

Vijay Ramamoorthi is a seasoned software architect with a background in artificial intelligence and machine learning. He has designed and implemented complex systems for Fortune 500 companies and has a passion for building scalable, reliable software solutions. His expertise spans cloud computing, microservices, and distributed systems. Vijay holds a Master's degree in Computer Science and a Bachelor's in Mathematics. 

Current Issue

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Submission Guidelines for the Journal of Computational Social Dynamics General Guidelines:

  1. Article Types: We accept a variety of article types including Original Research Articles, Review Papers, Short Reports, and Opinion Pieces.

  2. Language: Manuscripts must be written in English, and should be clear, concise, and free of jargon.

  3. Length: There is no strict word limit, but Original Research Articles should generally be between 4,000 and 10,000 words, including references.

  4. Formatting: Manuscripts should be submitted as a single Word or LaTeX document, formatted in double-spaced 12-point font.

  5. Abstract: An abstract of 250-300 words is required for all submissions, summarizing the key objectives, methods, findings, and implications of the research.

Manuscript Structure:

  • Title Page: Must include the title, author names, affiliations, and contact information for the corresponding author.

  • Introduction: Provide background, state the problem, and outline objectives.

  • Methods: Detail the methods and tools used in your research.

  • Results: Present the findings of your study.

  • Discussion: Interpret results, discuss their impact, and suggest future research directions.

  • Conclusion: Summarize the main points of the paper.

  • References: Citations should be formatted according to the APA/IEEE styles.

Ethical Guidelines:

Authors must ensure that their research adheres to ethical standards and that informed consent has been obtained for any human or animal subjects involved.

Plagiarism:

The Journal of Computational Social Dynamics uses plagiarism detection software. Any manuscript found to include plagiarized content will be rejected.

Peer Review Process:

All submissions undergo a double-blind peer review process. Authors can expect initial feedback within six to eight weeks.

Submission Process:
  1. Prepare your manuscript according to the guidelines.
  2. Submit your manuscript through our online portal at.
  3. After submission, you will receive a confirmation email with a manuscript ID for tracking purposes.
Revisions:

If revisions are requested, authors must resubmit the revised manuscript within the specified timeframe.

Publication Fees:

The journal has a nominal publication fee, waived for authors who lack funding. Details are available on our website.

For any questions or concerns, please contact the editorial office at editorial@vectoral.org. Thank you for considering the Journal of Computational Social Dynamics as a venue for your research.

Published by Vectoral Publishing, the Journal of Computational Social Dynamics maintains high standards in peer-review and scientific inquiry. Authors who wish to submit manuscripts should adhere to the guidelines detailed on our website, www.vectoral.org/jcsd. Vectoral Publishing does not bear any responsibility for the accuracy of information or for any outcomes related to the use of the research published. For editorial correspondence and submissions, please reach out to editorial@vectoral.org.