Proceedings of the International Conference on Artificial Intelligence and Secure Data Analytics (ICAISDA 2025)

<Previous Article In Volume
Next Article In Volume>

AI-Driven Framework for Intelligent SSD Management Using Machine Learning and Reinforcement Learning

Authors
Priyanshu Niranjan1, *, M. Thenmozhi2
1Toshiba Software India Private Limited, Bengaluru, 560034, India
2Puducherry Technological University, Puducherry, 605014, India
*Corresponding author. Email: priyanshu.niranjan@toshiba-tsip.com
Corresponding Author
Priyanshu Niranjan
Available Online 31 March 2026.
DOI
10.2991/978-94-6239-616-6_2How to use a DOI?
Keywords
Solid state drives; Q-learning; SMART logs; Reinforcement learning
Abstract

Solid-State Drives (SSDs) have transformed modern data storage through their superior speed, durability, and energy efficiency over traditional hard drives. However, as data-intensive and AI-powered applications proliferate, conventional SSD management techniques face limitations in scalability, adaptability, and longevity. Traditionally, SSDs rely on static, rule-based algorithms for core functions such as caching, wear leveling, and error prediction. These fixed algorithms operate with-out adapting to changing workloads or usage patterns, which can lead to inefficiencies and reduced device lifespan over time. The use of artificial intelligence (AI) in SSD management is a relatively new and emerging field, with much of the active research being proprietary and tightly guarded by major storage technology companies. This paper presents an AI-driven framework for optimizing SSD performance, reliability, and lifespan using machine learning and reinforcement learning approaches.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Artificial Intelligence and Secure Data Analytics (ICAISDA 2025)
Series
Advances in Intelligent Systems Research
Publication Date
31 March 2026
ISBN
978-94-6239-616-6
ISSN
1951-6851
DOI
10.2991/978-94-6239-616-6_2How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Priyanshu Niranjan
AU  - M. Thenmozhi
PY  - 2026
DA  - 2026/03/31
TI  - AI-Driven Framework for Intelligent SSD Management Using Machine Learning and Reinforcement Learning
BT  - Proceedings of the International Conference on Artificial Intelligence and Secure Data Analytics (ICAISDA 2025)
PB  - Atlantis Press
SP  - 5
EP  - 15
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-616-6_2
DO  - 10.2991/978-94-6239-616-6_2
ID  - Niranjan2026
ER  -