Enhancing NVMe SSD Performance through Intelligent Data Placement: An Analysis of Implementation and Benefits

Authors

  • Kasthuri Theja Peduru Arkansas State University, USA Author

DOI:

https://doi.org/10.32628/CSEIT25111267

Keywords:

NVMe SSD, Application-Aware Storage, Data Placement Optimization, Workload Characterization, Storage Performance Management

Abstract

Storage systems increasingly rely on NVMe SSDs for their superior performance characteristics, yet traditional static data placement strategies often fail to leverage their capabilities across diverse application workloads fully. This article comprehensively analyzes application-aware data placement in NVMe SSDs, exploring how workload-specific optimization can enhance storage performance. The core components of this article include workload characterization through read/write pattern analysis, strategic data placement optimization for both hot and cold data, and dynamic adaptation mechanisms for evolving workloads. This article addresses key implementation challenges such as processing overhead, protocol compatibility, and system scalability while highlighting potential benefits including improved I/O performance, reduced latency, and enhanced resource utilization. This article suggests that application-aware data placement represents a promising direction for optimizing NVMe SSD performance. However, careful consideration must be given to practical implementation constraints within existing NVMe standards and protocols.

Downloads

Download data is not yet available.

References

Qiumin Xu et al., "Performance analysis of NVMe SSDs and their implication on real world databases," ResearchGate, May 2015. Available: https://www.researchgate.net/publication/300298716_Performance_analysis_of_NVMe_SSDs_and_their_implication_on_real_world_databases

Shashikant Tank and Kumar Shukla, "A Comparative Analysis Of NVME SSD Classification Techniques: Performance, Efficiency, And Scalability," Journal of Emerging Technologies and Innovative Research, vol. 11, no. 5, May 2024. Available: https://www.jetir.org/papers/JETIR2405231.pdf

Jie Zhang et al., "Scalable Parallel Flash Firmware for Many-core Architectures," iUniversity of Wisconsin. Available: https://scail.cs.wisc.edu/papers/fast20-deepflash.pdf

Seungsu Baik et al., "Data Placement Through Clustering Sequential Writes and Isolating Cold Pages for Write Amplification Reduction in NAND Flash Memory," IEEE Access, 9 Oct. 2024. Available: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10701070

Flavio Villanustre et al., "Workload-Aware Data Placement for Cloud Computing," Academia, 2017. Available: https://www.academia.edu/68376997/Workload_Aware_Data_Placement_for_Cloud_Computing

Bharath Bhushan Sreeravindra, "Dynamic Data Storage Management Using Adaptive Cryptographic Key Mechanisms," International Journal of Engineering Research & Technology, vol. 13, no. 5, May 2024. Available: https://www.ijert.org/research/dynamic-data-storage-management-using-adaptive-cryptographic-key-mechanisms-IJERTV13IS050177.pdf

A. Gulati, I. Ahmad, and C. A. Waldspurger et al., "Understanding performance anomalies of SSDs and their impact in enterprise application environment," ACM Digital Library, 11 June 2012. Available: https://dl.acm.org/doi/10.1145/2254756.2254820

Runtao Wang et al., "Application-Aware Storage Strategy for Scientific Data," International Conference on E-Business Technology and Strategy, 2012. Available: https://link.springer.com/chapter/10.1007/978-3-642-34447-3_61

Mahsa Bayati et al., "Exploring Benefits of NVMe SSDs for BigData Processing in Enterprise Data Centers," 2019 5th International Conference on Big Data Computing and Communications (BIGCOM), Aug. 2019. Available: https://www.researchgate.net/publication/337501121_Exploring_Benefits_of_NVMe_SSDs_for_BigData_Processing_in_Enterprise_Data_Centers

Yan Wang et al., "Comprehensive Review of Storage Optimization Techniques in Blockchain Systems," Applied Sciences, vol. 15, no. 1, 30 Dec. 2024. Available: https://www.mdpi.com/2076-3417/15/1/243

Downloads

Published

13-01-2025

Issue

Section

Research Articles