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

TL;DR

This survey comprehensively analyzes SSD architecture, challenges, and device-level optimization techniques, providing insights into current solutions and future research directions for scalable, reliable, and secure SSDs.

Contribution

It offers a detailed overview of SSD components, challenges, and recent optimization techniques, highlighting open research issues and emerging architectures.

Findings

Error correction mechanisms improve reliability.

Enhanced FTL strategies extend SSD lifespan.

Emerging architectures like ZNS and FDP optimize performance.

Abstract

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.