mlsanityData to 14 Oct 2026

Device-Level Optimization Techniques for Solid-State Drives: A Survey

arXiv 2507.10573 ↗First posted 10 Jul 2025cs.ARcited by 1

Not on the map. Why?

Abstract (arXiv)

Solid-state drives (SSDs) have revolutionized data storage with their high performance, energy efficiency, and reliability. However, as storage demands grow, SSDs face critical challenges in scalability, endurance, latency, and security. This survey provides a comprehensive analysis of SSD architecture, key challenges, and device-level optimization techniques. We first examine the fundamental components of SSDs, including NAND flash memory structures, SSD controller functionalities (e.g., address mapping, garbage collection, wear leveling), and host interface protocols. Next, we discuss major challenges such as reliability degradation, endurance limitations, latency variations, and security threats. We then explore advanced optimization techniques, including error correction mechanisms, flash translation layer (FTL) enhancements, and emerging architectures like zoned namespace (ZNS) SSDs and flexible data placement (FDP). Finally, we highlight open research challenges, such as QLC/PLC NAND scalability, performance-reliability trade-offs, and SSD optimizations for AI/LLM workloads. This survey aims to guide future research in the development of next-generation SSDs that balance performance, endurance, and security in evolving storage ecosystems.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 10 Jul 2025.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.