Issue |
ITM Web Conf.
Volume 73, 2025
International Workshop on Advanced Applications of Deep Learning in Image Processing (IWADI 2024)
|
|
---|---|---|
Article Number | 03024 | |
Number of page(s) | 9 | |
Section | Blockchain, AI, and Technology Integration | |
DOI | https://doi.org/10.1051/itmconf/20257303024 | |
Published online | 17 February 2025 |
Optimizing Energy Efficiency and Green Storage in RAID-6 Systems: Comparative Analyses of Error Correction Codes
Department of Telecommunication Engineering, Xi'an Jiaotong-Liverpool University, Wenyuan Talent Apartments, Suzhou, Jiangsu, 215123, China
* Corresponding author email: Pinyi.Guo22@student.xjtlu.edu.cn
Redundant Array of Independent Disks Level 6 (RAID-6) systems are critical for ensuring fault tolerance and data reliability in data centers, leveraging dual-parity calculations for data protection. Despite their benefits, these systems are also associated with high energy consumption, significantly impacting the carbon footprint of data facilities. This study evaluates the energy efficiency of three prevalent error correction codes—Reed-Solomon, Row-Diagonal Parity (RDP), and Liberation Codes—applied within RAID-6 systems. Through detailed comparative analysis, the research assesses how each code influences power consumption and computational demands. Initial findings indicate that integrating more efficient coding algorithms could substantially lower energy usage, thus enhancing green computing efforts. Future research aims to implement these optimizations in actual storage setups within cloud and high-performance computing settings, potentially reducing both operational costs and environmental impacts. This proactive approach seeks to align with the increasing demand for sustainable data management practices, offering significant benefits in energy savings and reinforcing the commitment to eco-friendly computing solutions.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.